Informatization project comprehensive management method and system based on big data analysis

Abstract

The invention provides an informatization project comprehensive management method and system based on big data analysis, and the method comprises the steps: carrying out the intention analysis based on the obtained project earlier-stage demand data submitted by a user, obtaining the current project intention, comparing the current project intention with the project intention in historical project data, and obtaining a project duplicate checking report; carrying out novelty analysis based on the project duplicate checking report to obtain an analysis result, and if the analysis result shows that novelty reaches the standard, carrying out compliance verification on the earlier-stage demand data of the current project based on a pre-constructed management investment strategy form in combination with business architecture data and application architecture data corresponding to the current project to obtain a verification result; and if the verification result is successful, performing conflict identification on the project duplicate checking report based on the resource occupation data, the construction period data and the technical architecture data of the historical project to obtain a project conflict type and an associated historical project identifier. According to the invention, efficient, accurate and dynamic integrated management of informatization projects is realized.

Description

Technical Field

[0001] This invention relates to the field of computer technology, and in particular to a comprehensive management method and system for information technology projects based on big data analysis. Background Technology

[0002] As digital transformation deepens in large enterprises in the energy and power sectors, the number of IT projects is growing rapidly, and their management complexity is increasing significantly. To achieve standardized management and control over the entire project lifecycle, traditional IT project integrated management methods are gradually being established. The core of these methods is to centrally manage project initiation, investment planning, and execution through unified forms, process approvals, and manual reviews, aiming to alleviate problems such as fragmented processes and information silos that existed in the early stages.

[0003] However, existing integrated management methods for IT projects mainly rely on manual identification and assessment of project requirements, lacking effective data mining of historical projects and making it difficult to accurately determine the repetition and novelty of projects. At the same time, potential conflicts with existing projects in terms of resource allocation, technical architecture, and construction cycle are often not fully considered during the project planning stage, which can easily lead to frequent resource competition, schedule delays, or even project failures during execution. In addition, key aspects such as compliance review, conflict identification, and prioritization are often handled in a fragmented manner, lacking a unified data-driven mechanism and intelligent decision support. This makes it impossible to dynamically respond to complex and ever-changing business environments, resulting in difficulties in achieving systematic control over the entire project lifecycle, and consequently causing a chain of problems such as resource waste, schedule delays, and low return on investment. Summary of the Invention

[0004] This invention provides a comprehensive management method and system for information technology projects based on big data analysis, which solves the problems in the background technology caused by manual reliance, fragmented processes and lack of data collaboration, such as inaccurate deduplication, frequent conflicts, resource waste and control failure, and realizes efficient, accurate and dynamic comprehensive management of information technology projects throughout their entire life cycle.

[0005] In a first aspect, the present invention provides a comprehensive management method for information-based projects based on big data analysis, comprising: Based on the user-submitted preliminary project requirements data, intent is parsed to obtain the current project intent, and the current project intent is compared with the project intent in historical project data to obtain a project deduplication report; Based on the project plagiarism check report, a novelty analysis is performed to obtain the analysis results. If the analysis results indicate that the novelty meets the standards, then based on the pre-built management investment strategy form and the business architecture data and application architecture data corresponding to the current project, the compliance verification of the early requirements data of the current project is performed to obtain the verification results. If the verification result is passed, then based on the resource usage data, construction cycle data and technical architecture data of historical projects, conflict identification is performed on the project deduplication report to obtain the project conflict type and the associated historical project identifier. Then, based on the comprehensive score calculated for the current project and the projects to be executed, priority ranking is performed to obtain the ranking result. Based on the sorting results, project deduplication report, project conflict type and associated historical project identifier, and combined with the conflict handling rules data preset in the management investment strategy form, the conflict node solution is determined. Based on the sorting results, conflict node solutions, and the project schedule, resource usage, and management process dependencies of the project center, a comprehensive project management adjustment plan is obtained.

[0006] Optionally, the step of determining conflict resolution solutions based on sorting results, project deduplication reports, project conflict types, and associated historical project identifiers, combined with pre-defined conflict handling rules in the investment management strategy form, includes: Based on the priority number of the current project in the sorting result and the duplication identification information in the project duplication report, the location is identified to obtain the scheduling position of the current project in the queue of projects to be executed, and based on the scheduling position, it is determined whether the current project is in the critical interval of resource competition. If the scheduling location is in the critical range of resource competition, records are extracted based on the resource dimension indicated by the project conflict type and the associated historical project identifier to obtain conflict handling context records of multiple historical projects. Then, based on the conflict handling context records, historical handling strategy fragments that match the scheduling location of the current project are obtained. Based on the conflict resolution rule data in the management investment strategy form and the historical resolution strategy fragments, a set of conflict resolution rules applicable to the current project is obtained by matching the rules. Based on the handling trajectory corresponding to each rule in the conflict handling rule group and the associated historical project identifier, a conflict resolution path topology is constructed with the current project as the root node. Based on the conflict resolution path topology, the conflict handling rule group, and the management investment strategy form, the conflict node solution is determined.

[0007] Optionally, determining the conflict node solution based on the conflict resolution path topology, the conflict handling rule group, and the management investment strategy form includes: Based on the distribution characteristics of the in-degree and out-degree of nodes in the conflict resolution path topology, all node groups with branch selection capabilities in the topology are determined, and the nodes that have a decisive impact on the subsequent handling path are identified based on the node groups to obtain the key decision nodes. Based on the outgoing edges connected to the key decision nodes and their corresponding conflict resolution rule groups, multiple complete resolution paths from the current project to the historical project endpoint are determined, and based on the analysis of each complete resolution path, a corresponding multi-branch resolution plan draft is obtained. Based on the technical components that each solution in the draft multi-branch solution depends on and the technical architecture data of the current project, the architecture adaptation status of each solution is determined, and based on the architecture adaptation status, solutions with mutually exclusive architectures are eliminated to obtain candidate solutions. Based on the candidate solutions and the preset priority execution principles in the management investment strategy form, the execution priority order of each candidate solution is determined, and the candidate solution ranked first is determined as the conflict node solution.

[0008] Optionally, based on historical project resource usage data, construction cycle data, and technical architecture data, conflict identification is performed on the project deduplication report to obtain the project conflict type and associated historical project identifiers, including: Based on the historical project identifier groups that match the current project intent in the project deduplication report, extract the corresponding historical project resource usage data, historical project construction cycle data, and historical project technical architecture data. Based on all historical project resource usage data corresponding to the historical project identifier group, a resource usage topology structure group is constructed, and a topological isomorphism determination is performed between the resource usage topology structure group and the resource application topology structure in the project's early demand data to obtain a resource topology conflict identifier group. Based on the historical project construction cycle data corresponding to the resource topology conflict identifier group, a construction cycle time axis group is constructed, and the time axis intersection detection is performed between the construction cycle time axis group and the planned construction cycle time axis of the current project to obtain the time overlap conflict identifier group; the planned construction cycle time axis of the current project is constructed based on the project construction start and end time node information contained in the project's early requirements data; Based on the historical project technical architecture data corresponding to the time overlap conflict identifier group, a technical architecture component dependency graph group is constructed, and the component dependency path consistency is compared between the technical architecture component dependency graph group and the technical architecture component dependency graph of the current project to obtain the technical dependency conflict identifier group; the technical architecture component dependency graph of the current project is constructed with each technical component in the early requirements data of the project as a graph node and each dependency relationship as a directed edge; Based on the analysis of the technology dependency conflict identifier group and the project's early requirements data, the project conflict types and associated historical project identifiers are obtained.

[0009] Optionally, the analysis based on the technology dependency conflict identifier group combined with the project's early-stage requirements data yields the project conflict type and associated historical project identifiers, including: Based on the aforementioned technology dependency conflict identifier group, different types of conflicts are identified and analyzed to obtain a multidimensional conflict cross identifier group. Based on each historical project identifier in the multidimensional conflict cross identifier group, the conflict attribute combination in the three dimensions of resource topology, construction cycle and technical architecture is extracted to obtain a conflict feature triplet. Based on the conflict feature triples, conflict patterns are clustered and divided to obtain a conflict type mapping table. Based on the conflict type mapping table, each historical project identifier is assigned to a unique conflict type category to obtain a project conflict type allocation group. Based on the project conflict type allocation group, a conflict transmission chain is constructed, and based on the historical project identifier associated with each conflict type in the conflict transmission chain, a conflict impact propagation path group is determined. Based on the semantic constraint matching of the conflict impact propagation path group and the business objective description in the project's early requirements data, and based on the semantic constraint matching results, historical project identifiers that have irreconcilable constraints with the current project's business objectives are filtered out, thus obtaining the project conflict type and associated historical project identifiers.

[0010] Optionally, the identification and analysis of different types of conflicts based on the technology-dependent conflict identifier group to obtain a multidimensional conflict cross identifier group includes: Based on the aforementioned technology dependency conflict identifier group, technology dependency conflicts are classified into various conflict types; For each type of conflict, a multi-dimensional analysis is performed to obtain the analysis results of each dimension. The analysis results of each dimension are then integrated to obtain the multi-dimensional conflict cross-identification group. The multi-dimensional dimensions include time dimension, organizational dimension, technical dimension and business dimension.

[0011] Optionally, the project plagiarism report includes the similarity score between the current project and each historical project at the intent level, details of overlapping dimensions, and explanations of differences. Secondly, the present invention also provides an information-based project integrated management system based on big data analysis, applied to the information-based project integrated management method based on big data analysis as described in the first aspect; the information-based project integrated management system based on big data analysis includes: The intent parsing and deduplication module is used to parse the project's preliminary requirements data submitted by the user to obtain the current project intent, and compare the current project intent with the project intents in historical project data to obtain a project deduplication report; The novelty analysis and compliance verification module is used to perform novelty analysis based on the project duplication report and obtain the analysis results. If the analysis results show that the novelty meets the standard, the module will perform compliance verification on the preliminary requirement data of the current project based on the pre-built management investment strategy form and the business architecture data and application architecture data corresponding to the current project, and obtain the verification results. The conflict identification and priority ranking module is used to identify conflicts in the project deduplication report based on the resource consumption data, construction cycle data and technical architecture data of historical projects if the verification result is passed. It obtains the project conflict type and the associated historical project identifier, and prioritizes the projects to be executed based on the comprehensive score calculated by the current project to obtain the ranking result. The conflict node solution generation module is used to determine conflict node solutions based on sorting results, project deduplication reports, project conflict types and associated historical project identifiers, combined with the conflict handling rules data preset in the management investment strategy form. The solution integration module is used to integrate the sorting results, conflict node solutions, project schedule, resource usage and management process dependencies in the project center to obtain a comprehensive project management adjustment solution.

[0012] Thirdly, the present invention also provides an electronic device, comprising: a memory for storing computer software programs; and a processor for reading and executing the computer software programs, thereby realizing the comprehensive management method for information projects based on big data analysis as described above.

[0013] Fourthly, the present invention also provides a non-transitory computer-readable storage medium storing a computer software program, which, when executed by a processor, implements the comprehensive information project management method based on big data analysis as described above.

[0014] Fifthly, the present invention also provides a computer program product, including a computer program that, when executed by a processor, implements the comprehensive information project management method based on big data analysis as described above.

[0015] The comprehensive information project management method based on big data analysis provided in this invention analyzes the intent of user-submitted pre-project requirements data and compares it with historical project intents to generate a project duplication report. This effectively solves the problem of duplicate project initiation caused by manual judgment. Furthermore, novelty analysis is used to screen projects with genuine innovative value, avoiding ineffective investment. Compliance verification is performed by combining management investment strategy forms with the current project's business / application architecture data to ensure that projects meet regulatory requirements from the outset. After successful verification, the duplication report is used to perform in-depth conflict identification using historical project resource usage, construction cycle, and technical architecture data to accurately pinpoint potential conflict types and their relationships. The project is linked together, and then prioritized based on the comprehensive score to form a scientific and reasonable execution sequence. Finally, the conflict resolution solution is determined according to the conflict handling rules. The ranking results, solutions and the project center's schedule, resource status and process dependencies are integrated to generate a comprehensive project management adjustment plan. Based on this, a unified management mechanism is built, which is based on historical data, driven by intelligent analysis and aimed at dynamic coordination. This systematically solves the problems of inaccurate deduplication, frequent conflicts, resource waste and control failure caused by manual reliance, fragmented links and lack of data collaboration in the background technology. It realizes efficient, accurate and dynamic comprehensive management of the entire life cycle of information technology projects. Attached Figure Description

[0016] Figure 1 This is a flowchart illustrating the comprehensive management method for information technology projects based on big data analysis provided in this embodiment of the invention. Figure 2 This is a schematic diagram of the structure of the information project integrated management system based on big data analysis provided in an embodiment of the present invention; Figure 3 An embodiment diagram of the electronic device provided in this invention; Figure 4 An embodiment diagram of a computer-readable storage medium provided in accordance with the present invention. Detailed Implementation

[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0018] In the description of this invention, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the stated features. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0019] In the description of this invention, the term "for example" is used to mean "used as an example, illustration, or description." Any embodiment described as "for example" in this invention is not necessarily to be construed as being more preferred or advantageous than other embodiments. The following description is provided to enable any person skilled in the art to make and use the invention. Details are set forth in the following description for purposes of explanation. It should be understood that those skilled in the art will recognize that the invention can be made without using these specific details. In other instances, well-known structures and processes will not be described in detail to avoid obscuring the description of the invention with unnecessary detail. Therefore, the invention is not intended to be limited to the embodiments shown, but is consistent with the broadest scope of the principles and features disclosed herein.

[0020] See Figure 1 , Figure 1 This is a flowchart illustrating the comprehensive information project management method based on big data analysis provided by the present invention. In this embodiment, the executing entity of the comprehensive information project management method based on big data analysis is the project comprehensive management system. Therefore, the comprehensive information project management method based on big data analysis includes: Step 10: Based on the obtained user-submitted preliminary project requirements data, perform intent parsing to obtain the current project intent, and compare the current project intent with the project intent in historical project data to obtain a project deduplication report.

[0021] Optionally, the project integrated management system first obtains the preliminary project requirements data submitted by the user. This preliminary project requirements data includes key information such as the description of the project's core objectives, the energy and power business segments to which it belongs (e.g., generation-side management, transmission-side operation and maintenance, distribution-side services, integrated energy services, etc.), a list of functional requirements, the scope of service targets (e.g., power plant operation and maintenance teams, transmission line inspection teams, power user service centers, etc.), and expected outcome indicators (e.g., percentage improvement in operation and maintenance efficiency, reduction in energy consumption, and shortening of fault response time). Then, the obtained preliminary project requirements data is structured. Natural language processing technology is used to segment, tag, and extract key information from unstructured text-based requirements information. Based on a preset project intent classification system, the extracted key information is matched and categorized to parse and obtain the current project intent. The project intent classification system refers to the system built based on historical project data in the energy and power industry. It includes multiple primary categories such as digital operation and maintenance upgrades on the power generation side, construction of intelligent inspection platforms for transmission lines, optimization of user services on the distribution side, and establishment of a comprehensive energy data management and control center. Each primary category is further subdivided into multiple secondary subcategories. For example, digital operation and maintenance upgrades on the power generation side includes subcategories such as intelligent monitoring of generator unit status and refined management of power generation energy consumption.

[0022] Furthermore, after obtaining the current project intent through intent parsing, the project integrated management system first retrieves historical project data from the energy and power industry stored in the database. This historical project data includes complete data such as project intent, requirement details, construction information (e.g., unit type adaptation, power-specific technical architecture, outdoor operation and maintenance environment adaptation requirements), resource usage data, construction cycle, and technical architecture data for each historical project. Then, the parsed current project intent is compared with the project intents of each historical project across multiple dimensions, specifically including the overlap of core objectives, the matching degree of the energy and power business segment, the similarity of functional requirements, the consistency of service targets, and the suitability of adapted power equipment types. Based on the comparison results, a project deduplication report is generated. This report must clearly include the similarity score between the current project and each historical project at the intent level, details of overlapping dimensions, and explanations of differences. The similarity score can be calculated using a semantic understanding-based similarity algorithm. By constructing a vector space model of project intent, quantitative comparison at the intent level can be achieved, solving the problem of traditional methods relying on manual identification of requirements and difficulty in accurately judging project duplication.

[0023] In one embodiment, taking a power generation company under a large power group as an example, the project's preliminary requirements data are submitted through the project integrated management system. The requirements data are as follows: "In order to improve the operation and maintenance efficiency of coal-fired power generating units, build an intelligent monitoring platform for the status of generating units covering three main power plants, realize the functions of real-time collection of unit operating parameters, fault early warning and energy consumption analysis, and serve the power plant operation and maintenance teams and the group's production management department. It is expected to reduce the unplanned downtime rate of units by 15% and reduce power generation energy consumption by 3%."

[0024] After obtaining the requirement data, it was first structured to extract key information: the core objective is to improve the operation and maintenance efficiency of coal-fired power generating units and build an intelligent monitoring platform for generator unit status; the relevant energy and power business segment is generation-side management; the functional requirements are coverage of three major power plants, real-time collection of unit operating parameters, fault early warning, and energy consumption analysis; the service targets are power plant operation and maintenance teams and the group's production management department; the expected indicators are a 15% reduction in unplanned downtime rate and a 3% reduction in power generation energy consumption. Based on the preset project intent classification system, the current project intent was analyzed as "Digital Operation and Maintenance Upgrade of Generation Side - Construction of Intelligent Monitoring Platform for Generator Unit Status".

[0025] Next, historical project data from the energy and power industry was retrieved, including historical project A (intended for "Digital Operation and Maintenance Upgrade of the Generation Side - Construction of Intelligent Monitoring Platform for Generator Unit Status," with the core objective of monitoring the operating parameters of a single power plant's gas-fired generator unit, serving a single power plant operation and maintenance team, lacking group-level data aggregation and energy consumption analysis functions) and historical project B (intended for "Transmission Side Operation and Maintenance - Construction of Intelligent Inspection Platform for Transmission Lines," with the core objective of managing drone inspection data for 220kV transmission lines). The similarity score between the current project intent and the intents of each historical project was calculated using a vector space model. Specifically, the current project intent and the historical project intent were converted into vectors in a vector space, and the similarity score was obtained by calculating the cosine similarity between the two vectors. The calculated similarity score between the current project and historical project A was 82 points (out of 100), and the similarity score with historical project B was 35 points.

[0026] Finally, a project deduplication report is generated, detailing the overlapping dimensions: The overlapping dimensions between the current project and historical project A include the energy and power business segment (both are power generation side management) and core objectives and items (both are building intelligent monitoring platforms for generator unit status). The differences are explained as follows: 1. Different coverage: the current project covers three main power plants (coal-fired units), while historical project A only covers a single power plant (gas-fired unit); 2. Different functional scope: the current project includes group-level data aggregation and energy consumption analysis functions, while historical project A does not; 3. Different service targets: the current project includes the group's production management department, while historical project A only covers a single power plant operation and maintenance team; 4. Different expected indicators: the current project explicitly requires a 15% reduction in unplanned downtime and a 3% reduction in energy consumption, while historical project A only requires parameter monitoring without specific quantitative indicators.

[0027] Step 20: Perform a novelty analysis based on the project plagiarism check report to obtain the analysis results. If the analysis results indicate that the novelty meets the standards, then perform compliance verification on the preliminary requirement data of the current project based on the pre-built management investment strategy form and the business architecture data and application architecture data corresponding to the current project to obtain the verification results.

[0028] Optionally, the project management system, based on the obtained project plagiarism report, first performs a novelty analysis on the report. This determines whether the current project meets the novelty requirements for continued progress. If the requirements are not met, the project is terminated; otherwise, it proceeds to the next step. Specifically, the novelty analysis is based on a pre-defined novelty evaluation index system, comprehensively analyzing the similarity score, details of overlapping dimensions, and explanations of differences in the project plagiarism report to obtain the novelty analysis results. The novelty evaluation index system includes indicators such as the weight of core difference dimensions, similarity score threshold, and number of innovative points. The core difference dimensions are the sub-segments of the energy and power business segment, the implementation method of core functions, the scope of service targets, and the types of power equipment that are compatible with the project, which have a significant impact on the project's innovativeness. The preset similarity score threshold is 60 points (i.e., a similarity score below 60 points indicates significant core differences, a similarity score of 60 or above but below 85 points indicates partial overlap, and a similarity score of 85 or above indicates high overlap. This threshold is determined by analyzing the correlation between the degree of overlap of project intentions and the actual risk of duplication of construction, based on historical data statistics of more than 1,200 information technology projects in the energy and power industry over the past 5 years). This system aims to solve the problem that traditional methods lack historical data mining and are difficult to accurately judge the novelty of projects.

[0029] Furthermore, after the project integrated management system detects that the novelty meets the standard (i.e., there are two or more differences in the core difference dimension, the similarity score is less than 85 points, and there is one or more innovative functions or objectives), it retrieves the pre-built management investment strategy form. This form is formulated by the power group's project management department based on energy and power industry standards, national energy digital transformation policy requirements, and group investment control standards. It includes project compliance review clauses (such as power data security compliance requirements, energy industry informatization construction standards, environmental protection and energy consumption related standards, etc.), investment amount control scope, resource allocation standards (such as power dedicated servers, professional qualification requirements for operation and maintenance personnel, etc.). Simultaneously, business architecture data and application architecture data corresponding to the current project are retrieved from the connected database. The business architecture data includes the energy and power business process flowcharts corresponding to the project (such as generator unit operation and maintenance processes, data aggregation and reporting processes, etc.), business department collaboration relationships (such as the collaboration between power plant operation and maintenance teams and the group's production management department), and business data flow paths. The application architecture data includes the application system module divisions required by the project (such as parameter acquisition modules, fault early warning modules, energy consumption analysis modules, etc.), interface relationships between modules, and technology selection and adaptation requirements (such as hardware selection requirements for adapting to high-temperature and high-humidity outdoor power environments, and compatibility with the group's existing power data platform, etc.). Finally, based on the compliance review clauses in the management investment strategy form, the preliminary requirement data of the current project is verified for compliance. Verification includes whether the requirement data complies with national energy digital transformation policies, whether it meets power data security standards, whether it aligns with the group's information development plan, and whether the estimated investment amount is within the control range. The final compliance verification result is obtained to solve the problem of traditional methods where compliance review is handled separately from other stages.

[0030] Continuing with the above embodiments, after the project integrated management system obtains the project duplication report of the current project, it analyzes and concludes based on the preset novelty evaluation index system that: the similarity score between the current project and historical project A is 82 points (below the threshold of 85 points), there are 4 differences in the core difference dimensions (coverage scope, functional scope, service object scope, and expected indicators), and the "centralized monitoring of cross-power plant coal-fired unit status and group-level energy consumption analysis" proposed by the current project is an innovative goal (the historical projects have not achieved cross-power plant centralized management and energy consumption analysis functions). Therefore, the novelty analysis result is that the novelty meets the standard.

[0031] Next, the pre-built management investment strategy form was retrieved. The compliance review clauses in the form included "Energy and power information projects must comply with the 'Guidelines for Information Construction in the Power Industry'", "Power data collection and storage must meet the Level 3 requirements of the 'Power Data Security Management Measures'", "The estimated investment for group-level power generation-side information projects must be within the range of 8 million to 30 million yuan", and "Hardware selection must be suitable for the high-temperature and high-humidity operation and maintenance environment of power plants". At the same time, the business architecture data of the current project (including the operation and maintenance flowcharts of the three main coal-fired power plant units, the flow path of unit operation data to the group's production management department, and the description of the collaborative relationship between the power plant operation and maintenance team and the group's production management department) and application architecture data (including the system module division such as the unit parameter acquisition module, fault early warning algorithm module, energy consumption analysis module, and group-level data aggregation module, the RESTful interface relationship between modules, and the requirement that the technology selection must be compatible with the requirements of the group's existing power data platform).

[0032] Finally, based on the aforementioned management investment strategy form, business architecture data, and application architecture data, the compliance verification of the current project's preliminary requirements data was conducted: Upon verification, the current project requirements comply with the requirements of the "Guidelines for Information Technology Construction in the Power Industry"; the data acquisition and storage solution meets the Level 3 requirements of the "Power Data Security Management Measures"; the estimated investment based on the requirements is 20 million yuan, falling within the control range of 8 million to 30 million yuan; the hardware selection plan is suitable for the high-temperature and high-humidity environment of the power plant; and the business architecture and application architecture are compatible with the group's existing power data platform and align with the group's information technology development plan. Therefore, the compliance verification result is passed.

[0033] Step 30: If the verification result is passed, then based on the resource usage data, construction cycle data and technical architecture data of historical projects, the project deduplication report is used to identify conflicts, obtain the project conflict type and the associated historical project identifier, and prioritize the projects to be executed based on the comprehensive score calculated for the current project, and obtain the ranking result.

[0034] Optionally, after the verification result is passed, the project integrated management system retrieves the resource usage data, construction cycle data, and technical architecture data of historical projects from the database again. Based on this data, it identifies conflicts in the confirmed project deduplication report from three dimensions: resource usage, construction cycle, and technical architecture. Finally, it obtains the project conflict type and the associated historical project identifier, as shown in steps 301-305, in order to identify potential conflict issues that exist in the current project planning stage. The resource usage data includes hardware resources (models and quantities of power-specific servers, types of outdoor monitoring terminals, etc.), software resources (dedicated power data acquisition software, operation and maintenance management systems, etc.), human resources (number and specialization of power information technology developers, staffing with power plant operation and maintenance qualifications, etc.), and financial resources (amount of investment at each stage, etc.) used during the construction of historical projects. The construction cycle data includes the duration of each stage of historical projects, such as project initiation, development, testing, and online operation and maintenance (e.g., project implementation cycle planning considering the power industry's maintenance window). The technical architecture data includes the type of technical architecture used in historical projects (e.g., power-specific distributed architecture, edge computing architecture, etc.), core technical components (e.g., dedicated communication modules for power equipment, fault diagnosis algorithms, etc.), and data storage solutions (e.g., time-series database solutions adapted to massive amounts of real-time power data).

[0035] Furthermore, after identifying the project conflict type and associated historical project identifiers for the current project, the project integrated management system also needs to calculate the current project's comprehensive score. This comprehensive score calculation is based on a pre-set evaluation index system, which includes the project's alignment with the group's energy digital transformation strategy, expected benefits (such as reduced operation and maintenance costs, lower energy consumption, and reduced failure losses), technical feasibility (such as adaptability to the power field environment and compatibility with existing systems), and resource availability. Each index corresponds to specific quantitative calculation rules. After completing the calculation of the current project's comprehensive score, the system obtains a list of projects to be executed from the project integrated management platform (i.e., the project center). This list includes all energy and power information projects that have passed compliance verification but have not yet been launched, along with their comprehensive scores. Based on the comprehensive scores of each project, they are prioritized; the higher the comprehensive score, the higher the project priority. This final ranking result achieves unified data-driven compliance review, conflict identification, and priority ranking, solving the problem of fragmented processing of key aspects in traditional methods.

[0036] Continuing with the above examples, the evaluation indicators and quantitative calculation rules that can be used to calculate the comprehensive score of the current project are as follows: 1. Project strategic alignment (weight 0.4): The current project aligns with the Group's strategic plan of "digital transformation of power generation and cost reduction and efficiency improvement", scoring 96 points. This item's score = 96 × 0.4 = 38.4 points; 2. Expected benefit value (weight 0.3): Based on the expected reduction of unplanned outage rate by 15% and power generation energy consumption by 3%, the annual reduction in fault losses and energy costs is 12 million yuan, scoring 92 points. This item's score = 92 × 0.3 = 27.6 points; 3. Technical feasibility (weight 0.2): The technical solution is adapted to the high temperature and high humidity environment of the power plant and is compatible with the Group's existing power data platform, scoring 88 points. This item's score = 88 × 0.2 = 17.6 points; 4. Resource availability (weight 0.1): Except for conflicting server resources and some professional personnel, other resources have been secured, scoring 82 points. This item's score = 82 × 0.1 = 8.2 points. The overall score is 38.4 + 27.6 + 17.6 + 8.2 = 91.8 points. The list of projects to be executed is retrieved, which includes Project D (Intent: Construction of a distribution-side user service optimization platform, overall score 86.5 points) and Project E (Intent: Construction of a smart transmission line inspection data platform, overall score 93.2 points), etc. Based on the overall score, the priority is sorted as follows: Project E (93.2 points) > Current Project (91.8 points) > Project D (86.5 points) > ...

[0037] Step 40: Based on the sorting results, project deduplication report, project conflict type and associated historical project identifier, and combined with the conflict handling rules data preset in the management investment strategy form, determine the conflict node solution.

[0038] Optionally, after obtaining the project priority ranking results, project deduplication report, and identified project conflict types and associated historical project identifiers, the project integrated management system again calls the pre-built management investment strategy form to extract preset conflict resolution rule data from the form. This conflict resolution rule data is formulated based on the characteristics of energy and power industry projects, combined with conflict type, project priority, and associated historical project status, and includes the handling principles, optional solutions, and applicable conditions of solutions under different conflict scenarios (such as handling rules for conflicts during power plant maintenance windows and rules for the allocation of dedicated power resources). Finally, the system matches the corresponding optional solutions from the conflict resolution rule data to determine the conflict node solution, as detailed in steps 401-405.

[0039] Step 50: Based on the sorting results and conflict node solutions, the project schedule, resource usage and management process dependencies of the project center are integrated to obtain the comprehensive project management adjustment plan.

[0040] Optionally, after determining the project priority ranking results and conflict node solutions, the project integrated management system obtains the project center's project schedule, resource usage, and management process dependencies. The project schedule includes preset time nodes for each stage of the current project, task breakdown, responsible entities (such as the power information development team, power plant operation and maintenance cooperation team, etc.), and time planning to avoid power plant maintenance windows, etc. The resource usage includes details of resources already implemented for the current project, details of resources to be allocated / procured, and resource allocation time nodes, etc. The management process dependencies include the process connection relationship between the current project and other energy and power projects, the dependencies of each stage within the project, the group-level approval process nodes and sequence, and power safety review nodes, etc. The priority requirements corresponding to the ranking results are integrated into the project schedule, clarifying the current project's priority among pending energy and power information projects. This ensures that high-priority projects are prioritized in resource allocation, approval processes, and power safety reviews. Resource allocation plans, technical adaptation measures, and maintenance window avoidance plans from conflict node solutions are integrated into the project resource usage data, updating resource allocation details and timelines. Furthermore, based on management process dependencies, the connection between conflict node solution implementation and each project stage is analyzed, adjusting approval process nodes and sequences (e.g., synchronizing server procurement approval with power safety reviews) to ensure seamless integration of solutions and project management processes. Through these integration operations, a comprehensive project management adjustment plan is generated. This plan includes a revised project schedule, resource allocation plan, technical implementation details, approval process nodes, and conflict response plans (e.g., backup power equipment leasing plans for resource allocation delays), ultimately achieving systematic control throughout the project's entire lifecycle.

[0041] This invention, through intent analysis of user-submitted project pre-requisite data and comparison with historical project intents, generates a project duplication report. This effectively solves the problem of duplicate project initiation caused by manual judgment. Furthermore, novelty analysis filters out truly innovative projects, avoiding ineffective investment. Compliance verification is performed using a management investment strategy form and current project business / application architecture data to ensure projects meet regulatory requirements from the outset. After successful verification, the duplication report undergoes in-depth conflict identification using historical project resource usage, construction cycles, and technical architecture data to accurately pinpoint potential conflict types and their related projects. Finally, based on a comprehensive analysis... The projects to be executed are prioritized to form a scientific and reasonable execution sequence. Finally, the conflict resolution solution is determined according to the conflict handling rules. The prioritization results, solutions and the project center's schedule, resource status and process dependencies are integrated to generate a comprehensive project management adjustment plan. Based on this, a unified management mechanism is built with historical data as the foundation, intelligent analysis as the driving force and dynamic coordination as the goal. This systematically solves the problems of inaccurate deduplication, frequent conflicts, resource waste and control failure caused by manual reliance, fragmented processes and lack of data collaboration in the background technology. It realizes efficient, accurate and dynamic comprehensive management of the entire life cycle of information technology projects.

[0042] In one embodiment, the process of steps 301-305 includes: Step 301: Based on the historical project identifier group that matches the current project intent in the project deduplication report, extract the corresponding historical project resource usage data, historical project construction cycle data, and historical project technical architecture data.

[0043] Optionally, the project management system, based on the project deduplication report determined in step 10, filters out historical project identifier groups that match the current project's intent. These are historical projects whose similarity scores in the project deduplication report exceed a preset matching threshold (e.g., a preset matching threshold of 50 points, derived from historical data analysis). Each historical project identifier group is a unique set of numbers corresponding to this type of historical project (i.e., a set of associated historical project identifiers). After determining the historical project identifier group, based on this group, three types of core data are precisely extracted from the database: historical project resource usage data, historical project construction cycle data, and historical project technical architecture data. During the extraction process, precise matching is performed between the historical project identifier and the unique association field in the database to ensure the uniqueness and accuracy of the extracted data and avoid interference from irrelevant historical project data. Specifically, historical project resource usage data, historical project construction cycle data, and historical project technical architecture data correspond to details of various resources used during the construction of historical projects, the duration of each stage, and related technical architecture configurations, respectively.

[0044] Step 302: Based on all historical project resource usage data corresponding to the historical project identifier group, construct a resource usage topology structure group, and perform topology isomorphism determination based on the resource usage topology structure group and the resource application topology structure in the project's early demand data to obtain a resource topology conflict identifier group.

[0045] Optionally, after extracting all historical project resource usage data corresponding to the historical project identification group, the project integrated management system constructs a resource usage topology structure for each historical project, forming a resource usage topology structure group. The resource usage topology structure is a hierarchical topology structure with resource type as the first-level node, resource specific specifications as the second-level node, resource usage stage as the third-level node, and resource association relationships as directed edges. Resource types include four major categories: hardware resources, software resources, human resources, and financial resources. Resource association relationships represent the collaborative usage logic between different resources (such as the deployment association between "power dedicated server" and "power data acquisition dedicated software").

[0046] Next, based on the resource request information in the project's early requirements data, a resource request topology for the current project is constructed. This structure's hierarchical division and node definitions are completely consistent with the resource occupancy topology of historical projects to ensure the feasibility of subsequent comparisons. Then, each topology in the resource occupancy topology group is compared one by one with the resource request topology of the current project to determine if there is a topological isomorphism conflict. Specifically, the criteria for determining a topological isomorphism conflict are: if the overlap (i.e., isomorphic similarity) of the node hierarchy, node type and number, and directed edge relationships of the two topologies exceeds a preset conflict threshold (determined through topological analysis of core resources such as dedicated power servers and data acquisition systems; the preset conflict threshold in this solution is 70%), then a resource topology conflict is determined to exist. The identifiers of historical projects with resource topology conflicts are then compiled to form a resource topology conflict identifier group.

[0047] Furthermore, the formula for calculating isomorphic similarity is: ; in, For two topologies (Historical project resource usage topology) and Isomorphic similarity of (current project resource request topology): for The adjacency matrix, for The adjacency matrix, express The Middle The node and the first The association value of each node (1 if there is an association, 0 if there is no association); Similarly; For element-wise multiplication: This represents the total number of nodes in the topology. When... If the similarity is not found in the formula, it is determined that there is a resource topology conflict. This formula quantifies the degree of overlap between the resource topologies of two projects through the adjacency matrix of the topological structure. The numerator is the sum of the products of corresponding elements of the two adjacency matrices, representing the association relationship of overlapping nodes; the denominator is the maximum value of the sum of the elements of the two adjacency matrices, used for normalization, and finally obtains a similarity value of 0-100%.

[0048] Step 303: Based on the historical project construction cycle data corresponding to the resource topology conflict identifier group, construct a construction cycle time axis group, and perform time axis intersection detection based on the construction cycle time axis group and the planned construction cycle time axis of the current project to obtain the time overlap conflict identifier group; the planned construction cycle time axis of the current project is constructed based on the project construction start and end time node information contained in the project's early requirements data.

[0049] Optionally, after generating resource topology conflict identifier groups, the project integrated management system extracts the historical project construction cycle data corresponding to these identifier groups and constructs a construction cycle timeline for each associated historical project, forming a construction cycle timeline group. The construction cycle timeline is a linear time model with time as the horizontal axis and project construction stage as the vertical axis, clearly marking the start and end times (accurate to the day) and stage type (project initiation, development, testing, deployment, and maintenance, etc.) for each construction stage. Then, the system extracts project construction start and end time information (including the planned start and end times for each construction stage) from the project's early requirements data, and constructs the planned construction cycle timeline for the current project based on this information. This timeline model is completely consistent with the historical project construction cycle timelines. Finally, each timeline in the construction cycle timeline group is compared one by one with the planned construction cycle timeline for the current project to detect any overlap in time intervals. Specifically, the criteria for determining time overlap conflicts are as follows: if any construction phase time intervals in two timelines intersect (i.e., the end time of a certain phase of a historical project is greater than or equal to the start time of a certain phase of the current project, and the start time of a certain phase of a historical project is less than or equal to the end time of a certain phase of the current project), then a time overlap conflict is determined to exist. The identifiers of historical projects with time overlap conflicts are then compiled to form a time overlap conflict identifier group.

[0050] Step 304: Based on the historical project technical architecture data corresponding to the time overlap conflict identifier group, construct a technical architecture component dependency graph group, and compare the component dependency path consistency between the technical architecture component dependency graph group and the technical architecture component dependency graph of the current project to obtain the technical dependency conflict identifier group; the technical architecture component dependency graph of the current project is constructed with each technical component in the early requirements data of the project as a graph node and each dependency relationship as a directed edge.

[0051] Optionally, after identifying the time overlap conflict identifier group, the project integrated management system extracts the historical project technical architecture data corresponding to that identifier group. Then, it constructs a technical architecture component dependency graph for each associated historical project, forming a technical architecture component dependency graph group. This technical architecture component dependency graph is a directed graph with core components in the technical architecture as graph nodes and the dependencies between components (such as data transmission dependencies and function call dependencies) as directed edges. Each node is labeled with core information such as component name, model, and technical parameters, and each directed edge is labeled with dependency type and interaction protocol. Then, based on the technical component information and inter-component association requirements specified in the project's early requirements data, the current project's technical architecture component dependency graph is constructed. The construction rule is: each technical component in the project's early requirements data is used as a graph node, and the dependencies between components are used as directed edges. The node and edge labeling information is completely consistent with the historical project technical architecture component dependency graphs. Finally, each dependency graph in the technical architecture component dependency graph group is compared one by one with the technical architecture component dependency graph of the current project to detect whether there are consistency conflicts in the component dependency paths. The detection rule is as follows: if the two dependency graphs contain core components of the same functional type, but the component dependency paths (i.e., the connection relationships between directed edges between components) are inconsistent, and this path difference would cause data transmission anomalies, function call failures, or compatibility conflicts with the group's existing power data platform, then a technical dependency conflict is determined to exist. The identifiers of historical projects with technical dependency conflicts are summarized to form a technical dependency conflict identifier group.

[0052] Step 305: Based on the technology dependency conflict identifier group and the project's early requirements data, analyze the conflict types and associated historical project identifiers.

[0053] Optionally, the project integrated management system can perform multi-dimensional analysis based on the determined technical dependency conflict identification group and the core attributes of the project in the early stage of the project requirements data (such as project scale, amount of resources involved, technical complexity, etc.) to finally obtain the project conflict type and associated historical project identification, as shown in steps 3051-3054.

[0054] This invention employs a layered, multi-dimensional conflict identification logic to accurately focus on highly correlated historical projects, comprehensively covering core conflict areas such as resource topology, time overlap, and technological dependence. It clarifies the specific conflict types and impact levels of each related historical project, constructing a systematic conflict identification system adapted to the characteristics of the energy and power industry. This ensures that the final conflict identification results align with the actual construction scenarios and industry characteristics of projects, avoiding the problems of vague conflict identification scope, omission of key conflicts, and strong subjectivity inherent in traditional methods. It reduces resource competition and schedule delays caused by insufficient conflict prediction, improves the rationality of project resource allocation and construction efficiency, and realizes the transformation of conflict identification in energy and power information projects from subjective human judgment to data-driven accurate identification.

[0055] In one embodiment, the process of steps 3051-3054 includes: Step 3051: Based on the technology dependency conflict identifier group, identify and analyze different types of conflicts to obtain a multi-dimensional conflict cross identifier group. Based on each historical project identifier in the multi-dimensional conflict cross identifier group, extract the combination of conflict attributes in the three dimensions of resource topology, construction cycle and technical architecture to obtain a conflict feature triplet.

[0056] Optionally, after generating the technology dependency conflict identifier group, the project integrated management system first conducts a multi-dimensional conflict cross-identification analysis based on the technology dependency conflict identifier group, as detailed in steps 30511-30512. After determining the multi-dimensional conflict cross-identification group, for each historical project identifier in the identifier group, conflict attributes are extracted in the resource topology dimension, construction cycle dimension, and technical architecture dimension to form a conflict attribute combination. Specifically, the resource topology dimension conflict attributes include resource type overlap and resource association conflict level; the construction cycle dimension conflict attributes include the proportion of overlapping time duration and overlapping stage type; and the technical architecture dimension conflict attributes include component dependency path difference and protocol adaptation conflict level. The conflict attributes of the three dimensions are combined in the format "(resource topology conflict attribute, construction cycle conflict attribute, technical architecture conflict attribute)" to obtain the conflict feature triplet corresponding to each historical project identifier. The conflict feature triplets of all historical project identifiers constitute a conflict feature triplet.

[0057] Step 3052: Cluster the conflict patterns based on the conflict feature triples to obtain a conflict type mapping table, and assign each historical project identifier to a unique conflict type category based on the conflict type mapping table to obtain the project conflict type allocation group.

[0058] Optionally, after obtaining the conflict feature triples, the project integrated management system uses a density-based clustering algorithm (DBSCAN, where the core neighborhood radius and minimum sample size parameters are adaptively determined based on the statistical characteristics of historical project conflict data) to cluster the conflict feature triples. During clustering, the quantified values ​​of each dimension attribute in the conflict feature triples are used as feature vectors, and the Euclidean distance between feature vectors is calculated to determine clusters. Each cluster corresponds to a typical conflict pattern. After clustering, a unique conflict type category is assigned to each cluster, and a conflict type mapping table is constructed. This mapping table records the one-to-one correspondence between clusters and conflict type categories, as well as the core feature descriptions of each category. Then, based on the conflict type mapping table, each historical project identifier in the multi-dimensional conflict cross-identification group is assigned to its corresponding conflict type category, forming a project conflict type allocation group. The conflict type categories are divided into three types based on the clustering results and the characteristics of energy and power industry projects: resource-time-technology composite conflict, resource-technology composite conflict, and time-technology composite conflict.

[0059] Step 3053: Based on the project conflict type allocation group, construct the conflict transmission chain, and based on the historical project identifier associated with each conflict type in the conflict transmission chain, determine the conflict impact propagation path group.

[0060] Optionally, after obtaining the generated project conflict type allocation group, the project integrated management system constructs a conflict transmission chain based on the resource sharing relationships, technical connections, and construction cycle connections of energy and power industry projects. This conflict transmission chain is a directed graph with conflict type categories as nodes and conflict transmission relationships as directed edges. The conflict transmission relationship refers to the associated influence relationship between one conflict type and other conflict types caused by resource contention, technical incompatibility, or time overlap. After construction, for each conflict type category in the conflict transmission chain, all associated historical project identifiers are extracted. Based on the resource dependence, technical coupling, and time overlap between historical and current projects, a path search algorithm (such as depth-first search) is used to determine the propagation path of the impact of each historical project conflict on the current project. All impact propagation paths constitute a conflict impact propagation path group. The judgment logic for the impact propagation path is: each node in the path corresponds to a conflict type with a direct transmission relationship, and the path endpoint is the core construction stage of the current project (such as core function development, key resource allocation, and online operation and maintenance).

[0061] Step 3054: Perform semantic constraint matching between the conflict impact propagation path group and the business objective description in the project's early requirements data, and filter out historical project identifiers that have irreconcilable constraints with the current project's business objectives based on the semantic constraint matching results, thereby obtaining the project conflict type and associated historical project identifiers.

[0062] Optionally, after obtaining the conflict impact propagation path group, the project integrated management system extracts business objective description information from the project's early-stage requirements data. This information includes core constraints such as the project's core business functions, key performance indicators, construction timelines, and technical compatibility standards. Subsequently, a semantic similarity-based matching algorithm is used to semantically match each path in the conflict impact propagation path group with the business objective description. The core logic of this semantic constraint matching is: semantically segmenting and feature matching the impact content of the conflict impact propagation path (such as delays in core function development due to resource contention, or data collection failures due to technical incompatibility) with the constraints of the business objective description, and calculating the matching similarity. When the matching similarity is lower than a preset semantic matching threshold (determined through semantic analysis of historical conflict cases; this solution presets it to 60%), it is determined that the conflict corresponding to that path has an irreconcilable constraint with the current project's business objective. Finally, historical project identifiers corresponding to the irreconcilable constraints are selected, and combined with their respective conflict type categories, the project conflict type and associated historical project identifiers for the current project are determined.

[0063] This invention achieves a precise upgrade in the determination of conflict types in energy and power information projects from a single-dimensional integration to a multi-dimensional collaborative analysis. Through the logic of conflict feature extraction, pattern clustering, transmission chain construction, and semantic constraint matching, it accurately depicts the multi-dimensional characteristics and impact transmission paths of conflicts in each historical project, clarifies the reconciliation between the conflict and the current project's business objectives, and enables the finally determined project conflict types and associated historical project identifiers to accurately match the actual construction needs and industry characteristics of the project. This avoids the problems of vague type classification, one-sided impact assessment, and neglect of business objective adaptability in traditional conflict determination.

[0064] In one embodiment, the process of steps 30511-30512 includes: Step 30511: Classify the technology dependency conflicts based on the technology dependency conflict identifier group to obtain multiple conflict types.

[0065] Optionally, the project integrated management system categorizes the technical dependency conflicts corresponding to each historical project identifier in the technical dependency conflict identifier group based on the core causes and scope of impact, resulting in multiple conflict types. The classification criteria for technical dependency conflicts are as follows: using the conflict dimension of the technical architecture component dependency graph as the core classification benchmark, and combining the characteristics of the energy and power industry's technical architecture, technical dependency conflicts are divided into three typical conflict types: protocol adaptation conflicts, component dependency path conflicts, and data interaction conflicts. Protocol adaptation conflicts refer to technical dependency conflicts where the core communication protocols of historical projects and current projects are incompatible, leading to interface adaptation failures with the group's existing power data platform. Component dependency path conflicts refer to technical dependency conflicts where the core components of historical projects and current projects are the same, but the dependency paths between components differ significantly, leading to conflicts in functional call logic. Data interaction conflicts refer to technical dependency conflicts where the data interaction formats and data transmission rates of the core components of historical projects and current projects are mismatched, leading to data loss or transmission delays. During the classification process, the core features of the technical architecture data (communication protocol type, component dependency path, data interaction parameters) corresponding to each historical project identifier are extracted and matched with the core features of the three conflict types mentioned above. The technical dependency conflict of each historical project identifier is assigned to a unique corresponding conflict type, thus completing the classification of technical dependency conflicts and obtaining multiple conflict types and a subset of historical project identifiers corresponding to each type.

[0066] Step 30512: Perform multi-dimensional analysis for each type of conflict, obtain the analysis results of each dimension, and integrate the analysis results of each dimension to obtain a multi-dimensional conflict cross-identification group; the multi-dimensional dimensions include time dimension, organizational dimension, technical dimension and business dimension.

[0067] Optionally, after determining the classification of technical dependency conflicts, the project integrated management system conducts multi-dimensional analysis for each subset of historical project identifiers corresponding to each conflict type. These multi-dimensional analyses include time, organization, technology, and business dimensions. The analysis content for each dimension is as follows: For the time dimension, the system analyzes the temporal correlation between the project construction phase corresponding to the technical dependency conflict in the historical project and the planned construction phase of the current project. The core analysis indicator is the percentage overlap between the conflict's impact period and the current project's core construction phase. For the organization dimension, the system analyzes the organizational affiliation and resource allocation authority between the implementing entities of the historical project and the current project. The core analysis indicator is the organizational coordination coefficient (representing the resource sharing and collaborative capabilities of the two implementing entities). For the technology dimension, the system analyzes the technical difficulty of resolving the technical dependency conflict in the historical project and its impact on the current project's technical architecture, i.e., the percentage of technical resources required to resolve the conflict. For the business dimension, the system analyzes the impact of the technical dependency conflict in the historical project on the realization of the current project's core business functions. The core analysis indicator is the business impact weight (representing the probability that the conflict will prevent the realization of the current project's core business functions). The formula for calculating the organizational coordination coefficient is: ; in, The organizational synergy coefficient; This is the set of organizational structure nodes for the current project implementation entity. This is a set of organizational structure nodes for the main body implementing historical projects. This is the set of resource scheduling permissions for the current project implementation entity; This represents the set of resource scheduling permissions of the implementing entities of historical projects. Based on the intersection and union operations of set theory, this formula quantifies the organizational collaboration capabilities of the two implementing entities. The numerator is the size of the intersection of organizational structure nodes and resource scheduling permissions, representing the basis for collaboration; the denominator is the size of the union of the two, representing the total scope of collaboration. The closer the result is to 1, the stronger the collaboration capability.

[0068] Furthermore, for each type of conflict, core analytical indicator data for each dimension of the corresponding historical project identifier subset are extracted, and the analysis results are obtained for each dimension. Then, the analysis results for each dimension are integrated. The integration logic is as follows: historical project identifiers with a time dimension overlap duration ≥ 50%, an organizational dimension synergy coefficient ≤ 0.4, a technical dimension resolution cost coefficient ≥ 0.6, and a business dimension impact weight ≥ 0.5 are selected. The technical dependency conflicts corresponding to these identifiers have a strong multi-dimensional correlation with the current project. The 50%, 0.4, 0.6, and 0.5 are determined based on the correlation analysis of the four dimensions of time, organization, technology, and business, respectively. The selected historical project identifiers are then intersected with the resource topology conflict identifier group generated in step 302 and the time overlap conflict identifier group generated in step 303. The final set of intersection identifiers is the multi-dimensional conflict cross-identity identifier group.

[0069] This invention achieves a deep transformation from general identification of technology dependency conflicts to precise classification and multi-dimensional association. Through the characteristic classification of technology dependency conflicts and the collaborative analysis of time, organization, technology, and business dimensions, it accurately screens out conflict identifiers that have strong multi-dimensional associations with the current project, clarifies the core association attributes of the multi-dimensional conflict cross-identifiers, and enables the final multi-dimensional conflict cross-identifier group to accurately match the construction scenario and industry characteristics of the current project, avoiding the problems of fuzzy classification, single association dimension, and low screening accuracy in traditional multi-dimensional conflict cross-identification.

[0070] In one embodiment, the process of steps 401-405 includes: Step 401: Based on the priority number of the current project in the sorting result and the duplication identification information in the project duplication report, the position of the current project in the queue of projects to be executed is identified, and the scheduling position is used to determine whether the current project is in the critical interval of resource competition.

[0071] Optionally, the project management system extracts the priority number of the current project from the sorting results. This priority number represents the current project's position in the sorting sequence (the first-ranked project has a priority number of 1, increasing sequentially). Simultaneously, it extracts duplication identification information from the project deduplication report. This information represents the maximum similarity score between the current project and each historical project, along with the corresponding number of historical projects, indicating the degree of homogeneity between the current and historical projects. Then, the priority number of the current project is mapped to the scheduling sequence of the queue of projects to be executed, obtaining the scheduling position of the current project within that queue. The scheduling position is represented as "priority number - homogeneity level," where the homogeneity level is based on the maximum similarity score in the duplication identification information: a maximum similarity score ≥ 85% indicates a high homogeneity level, 60% ≤ maximum similarity score < 85% indicates a medium homogeneity level, and a maximum similarity score < 60% indicates a low homogeneity level. After identifying the scheduling position, based on preset resource competition critical interval rules, it is determined whether the current project's scheduling position is within the resource competition critical interval. The resource competition critical interval is a scheduling region in the queue of projects to be executed that has high overlap in resource requirements, dense priorities, and a high degree of homogeneity. Its determination rule is based on the total number N in the queue of projects to be executed: the region where the priority number corresponding to the scheduling position is in the interval [2, ceil(N×30%)] (ceil is the floor function) and the homogeneity level is medium or high is considered the resource competition critical interval. If the scheduling position of the current project simultaneously satisfies the condition that the priority number is within the above interval and the homogeneity level is medium or high, it is determined to be in the resource competition critical interval; otherwise, it is determined not to be in it. For current projects not in the resource competition critical interval, it indicates that resource competition is weak or unnecessary, and therefore, conflict node resolution is not required.

[0072] Step 402: If the scheduling location is in the critical range of resource competition, records are extracted based on the resource dimension indicated by the project conflict type and the associated historical project identifier to obtain conflict handling context records of multiple historical projects. Based on the conflict handling context records, historical handling strategy fragments that match the scheduling location of the current project are obtained.

[0073] Optionally, once the project integrated management system determines that the current project is in a critical range of resource competition, it retrieves the corresponding conflict resolution context record from the corresponding database based on the resource dimension indicated by the determined project conflict type and the associated historical project identifier. The resource dimension indicated by the project conflict type refers to the core resource category involved in the conflict (such as power-specific hardware resources, power information human resources, and technical architecture resources). The conflict resolution context record is a complete record of the resolution of similar conflict types and resource dimensions formed during the construction process of historical projects, including core content such as the conflict scenario, conflict resolution objectives, resource allocation plan, technical adaptation measures, resolution implementation process, resolution effect evaluation, and dispatch location information. After extracting the conflict resolution context records, all extracted conflict resolution context records are filtered based on the current project's scheduling location. The filtering logic is as follows: select record segments from historical resolution context records where the matching degree between the scheduling location of the historical project and the current project's scheduling location is ≥70%. The scheduling location matching degree is calculated using a location feature-based similarity algorithm, specifically a weighted summation model that combines priority sequence similarity and homogeneity level matching values ​​to quantify the similarity between the current project and historical projects' scheduling scenarios. The calculation formula is as follows: ;in, For scheduling location matching degree; The weighting coefficient (set based on experience in project scheduling in the energy and power industry, such as a preset value of 0.6). This is the priority number of the current project; This refers to the priority number of historical projects; Homogeneity level of historical projects Homogeneity level with current projects The type matching value is 1 for the same level, 0.5 for adjacent levels, and 0 for non-adjacent levels. The filtered record fragments are the historical handling strategy fragments that match the current project scheduling position. Each fragment contains the core conflict handling measures and resource scheduling logic of the corresponding historical project.

[0074] Step 403: Based on the conflict resolution rule data in the management investment strategy form, perform rule matching with historical resolution strategy fragments to obtain a set of conflict resolution rules applicable to the current project.

[0075] Optionally, after selecting the historical handling strategy fragments, the project integrated management system retrieves a pre-built management investment strategy form and extracts conflict handling rule data from it. The conflict handling rule data is a standardized set of handling rules based on the characteristics of energy and power industry projects, combined with dimensions such as conflict type, resource dimension, and scheduling location. Each rule includes core elements such as the applicable scenario, core handling requirements, resource control threshold, and technical adaptation standards. Next, the historical handling strategy fragments are matched with the conflict handling rule data. The matching dimensions include four core dimensions: consistency of conflict type, correlation of resource dimension, adaptability of scheduling location, and compliance with industry standards. For each historical handling strategy fragment, all matching conflict handling rules are obtained. Finally, all matched rules are deduplicated, removing duplicate rules and rules that conflict with the core needs of the current project (such as rules where the resource control threshold exceeds the current project's investment estimate). The final set of rules is the conflict handling rule group applicable to the current project.

[0076] Step 404: Based on the handling trajectory corresponding to each rule in the conflict handling rule group and the associated historical project identifier, construct a conflict resolution path topology with the current project as the root node.

[0077] Optionally, after obtaining the conflict resolution rule set, the project integrated management system extracts the core resolution requirements corresponding to each rule and retrieves the resolution trajectory corresponding to the associated historical project identifier. This trajectory records the execution order, resource flow path, technical implementation process, and dependencies of each stage in the conflict resolution process of historical projects. Then, using the current project as the root node, a conflict resolution path topology is constructed. This topology is a directed acyclic graph, with node types including the root node (current project), core resolution measure nodes (determined based on the core requirements of the conflict resolution rule set), resource nodes (various resources required for resolution), technical implementation nodes (technical adaptation measures), and constraint nodes (maintenance windows, resource control thresholds, etc.). Directed edges represent the dependencies between nodes (e.g., core resolution measure nodes depend on resource nodes, and technical implementation nodes must meet constraint node requirements). During the construction process, the reasonable execution logic from the historical project resolution trajectories is integrated into the edge relationship definition of the topology to ensure the feasibility and industry adaptability of the path.

[0078] Step 405: Based on the conflict resolution path topology, conflict handling rule group, and management investment strategy form, determine the conflict node solution.

[0079] Optionally, the project integrated management system generates a solution based on the constructed conflict resolution path topology, the obtained conflict handling rule group, and the management investment strategy form, thus obtaining a conflict node solution, as detailed in steps 4051-4054.

[0080] This invention realizes the transformation of conflict handling in energy and power information projects from experience-driven to rule-based and path-based precise decision-making. Through scheduling location identification, historical strategy screening, rule matching, topology construction and solution refinement, it accurately matches the priority, conflict type, resource dimension and industry characteristics of the current project, and constructs a visualized conflict resolution path with the current project as the core. This enables the final conflict node solution to take into account resource management requirements, technical adaptation standards and maintenance window constraints, avoiding the problems of insufficient targeting, resource waste and disconnection from project scheduling priorities in the formulation of traditional conflict handling solutions.

[0081] In one embodiment, the process of steps 4051-4054 ​​includes: Step 4051: Based on the distribution characteristics of the in-degree and out-degree of nodes in the conflict resolution path topology, determine all node groups with branch selection capabilities in the topology, and identify the nodes that have a decisive impact on the subsequent handling path based on the node groups to obtain the key decision nodes.

[0082] Optionally, the project integrated management system, based on the constructed conflict resolution path topology, first extracts the in-degree and out-degree data of each node in the topology. The in-degree of a node is the number of directed edges pointing to that node, representing the degree to which the node is influenced by other nodes; the out-degree of a node is the number of directed edges originating from that node, representing the range of influence that node has on subsequent nodes. Then, based on the distribution characteristics of node in-degree and out-degree, all node groups with branch selection capabilities in the topology are identified. Nodes with branch selection capabilities are those with an out-degree ≥ 2, meaning that the node can guide the resolution path to extend in multiple different directions; the set of such nodes constitutes the node group with branch selection capabilities. A node influence weighting algorithm is then used to screen the node groups with branch selection capabilities, identifying key decision nodes that have a decisive impact on subsequent resolution paths. The core criteria for determining key decision nodes are: a node influence weight ≥ 0.6, and the resolution path corresponding to the outgoing edges of the node covers the core objectives of the current project conflict resolution (such as resource conflict resolution, technical adaptation completion, and time conflict avoidance). The calculation formula for the node influence weighting algorithm is as follows: ; in, The influence weight of node v; Let v be the out-degree of node v; Let v be the set of all subsequent nodes pointed to by the outgoing edges of node v; The importance coefficient for subsequent node u (set based on node type: such as 0.8 for core handling measures nodes, 0.6 for resource nodes, 0.7 for technical implementation nodes, and 0.5 for constraint nodes). This is the set of all nodes in the conflict resolution path topology. The formula quantifies the influence of a node on the conflict resolution path based on the product of its out-degree (range of influence) and the importance coefficient of subsequent nodes. After normalization, weight values ​​of 0-1 are obtained, and nodes with a weight ≥ 0.6 are identified as key decision nodes.

[0083] Step 4052: Based on the outgoing edges connected to the key decision nodes and their corresponding conflict resolution rule groups, determine multiple complete resolution paths from the current project to the historical project endpoint, and based on the analysis of each complete resolution path, obtain the corresponding multi-branch resolution plan draft.

[0084] Optionally, after identifying key decision nodes, the project integrated management system extracts all outgoing edges connected to each key decision node and, in conjunction with the conflict resolution rule group, clarifies the constraint requirements of the resolution rules corresponding to each outgoing edge. Then, starting from the root node corresponding to the current project and ending at the conflict resolution endpoint corresponding to the associated historical project identifier, a depth-first search algorithm is used to traverse the topology, generating multiple complete resolution paths. A complete resolution path is a sequence of directed edges starting from the root node, passing through key decision nodes, and finally reaching the conflict resolution endpoint of the historical project, with each node in the path meeting the requirements of the corresponding conflict resolution rule. Each complete resolution path undergoes structured analysis, transforming the node information (resolution measures, resources, technical requirements, constraints) into executable solution content, resulting in a multi-branch resolution plan draft for each complete resolution path. Each draft plan includes core resolution measures, detailed resource requirements, technical implementation standards, timeline requirements, and constraints.

[0085] Step 4053: Based on the technical components that each solution in the multi-branch handling plan draft depends on and the technical architecture data of the current project, determine the architecture adaptation status of each solution, and eliminate the handling solutions with mutually exclusive architectures based on the architecture adaptation status to obtain candidate solutions.

[0086] Optionally, after obtaining the draft multi-branch handling solutions, the project integrated management system extracts a list of technical components upon which all handling measures in each draft solution depend, and simultaneously retrieves the current project's technical architecture data (including core technical components, component interface standards, and architecture compatibility requirements). The technical component lists of each draft solution are compared with the current project's technical architecture data to determine the architecture compatibility status of each solution. The architecture compatibility status is categorized into three types: compatible, partially compatible, and incompatible. For compatible: all technical components of the solution meet the compatibility requirements of the current project's technical architecture, and component interfaces can be directly connected. For partially compatible: the core technical components of the solution meet the compatibility requirements, but non-core components require minor modifications. For incompatible: the solution has core technical components that are mutually exclusive with the current project's technical architecture, or component interfaces that cannot be connected. Finally, based on the architecture compatibility status, the draft multi-branch handling solutions are eliminated. The elimination rule is: retain compatible and partially compatible draft solutions, and eliminate incompatible draft solutions. The remaining draft solutions after elimination are the candidate solutions.

[0087] Step 4054: Based on the candidate solutions and the preset priority execution principles in the management investment strategy form, determine the execution priority order of each candidate solution, and identify the candidate solution ranked first as the conflict node solution.

[0088] Optionally, after obtaining candidate solutions, the project integrated management system retrieves the management investment strategy form and extracts the preset priority execution principles from the form. These priority execution principles are set based on the characteristics of project management in the energy and power industry, with the core priority ranking as follows: 1. Priority of resource input economics (the lower the proportion of resource input to the current project investment estimate, the higher the priority); 2. Priority of technical implementation difficulty (the less technical modification and the shorter the implementation cycle, the higher the priority); 3. Priority of time adaptability (the higher the degree of fit between the solution's execution time and the maintenance window and project plan cycle, the higher the priority). Then, based on the above priority execution principles, a multi-dimensional priority ranking algorithm is used to determine the execution priority order of each candidate solution. During the ranking process, there is no need to calculate weighted scores; the solutions are directly compared according to the hierarchy of priority execution principles. The comparison process is as follows: first, the economics of resource input are compared, with solutions with lower resource input ratios ranked higher; if the resource input ratios are the same, then the technical implementation difficulty is compared, with solutions with lower implementation difficulty ranked higher; if the technical implementation difficulty is the same, finally, time adaptability is compared, with solutions with higher adaptability ranked higher. The candidate solution ranked first will be determined as the final solution to the conflict node. Details such as the implementing entity, specific time nodes, and division of responsibilities will be supplemented and improved to ensure that the solution can be implemented.

[0089] This invention achieves a precise upgrade of conflict resolution solutions for energy and power information projects from a single generation to multi-branch optimization and screening. Through the entire process of key decision node identification, multi-path solution generation, architecture adaptability screening, and priority ranking, it accurately identifies the core decision points in the conflict resolution path, comprehensively covers potential feasible solutions, eliminates invalid solutions with mutually exclusive architectures, and ensures that the final solution meets the technical architecture requirements and investment control principles. This makes the determined conflict node solutions feasible, economical, and adaptable, avoiding the problems of single path, ignoring architecture compatibility risks, and uncontrolled resource investment in traditional solution formulation, thereby improving the success rate of solution implementation and the efficiency of conflict resolution.

[0090] Furthermore, the integrated management system for information technology projects based on big data analysis provided by the present invention will be described below. The integrated management system for information technology projects based on big data analysis described below can be referred to in correspondence with the integrated management method for information technology projects based on big data analysis described above.

[0091] Optional, refer to Figure 2 , Figure 2 This is a schematic diagram of the structure of the information project integrated management system based on big data analysis provided by the present invention. The information project integrated management system based on big data analysis includes: The intent parsing and deduplication module 210 is used to parse the intent based on the user-submitted preliminary project requirements data, obtain the current project intent, and compare the current project intent with the project intent in historical project data to obtain a project deduplication report. The novelty analysis and compliance verification module 220 is used to perform novelty analysis based on the project duplication report and obtain the analysis results. If the analysis results show that the novelty meets the standard, the module will perform compliance verification on the preliminary requirement data of the current project based on the pre-built management investment strategy form and the business architecture data and application architecture data corresponding to the current project, and obtain the verification results. The conflict identification and priority ranking module 230 is used to identify conflicts in the project deduplication report based on the resource consumption data, construction cycle data and technical architecture data of historical projects if the verification result is passed, to obtain the project conflict type and the associated historical project identifier, and to prioritize the projects to be executed based on the comprehensive score calculated by the current project, and to obtain the ranking result. The conflict node solution generation module 240 is used to determine the conflict node solution based on the sorting results, project deduplication report, project conflict type and associated historical project identifier, combined with the conflict handling rule data preset in the management investment strategy form; The solution integration module 250 is used to integrate the sorting results, conflict node solutions, project schedule, resource usage and management process dependencies in the project center to obtain a comprehensive project management adjustment solution.

[0092] This invention, through intent analysis of user-submitted project pre-requisite data and comparison with historical project intents, generates a project duplication report. This effectively solves the problem of duplicate project initiation caused by manual judgment. Furthermore, novelty analysis filters out truly innovative projects, avoiding ineffective investment. Compliance verification is performed using a management investment strategy form and current project business / application architecture data to ensure projects meet regulatory requirements from the outset. After successful verification, the duplication report undergoes in-depth conflict identification using historical project resource usage, construction cycles, and technical architecture data to accurately pinpoint potential conflict types and their related projects. Finally, based on a comprehensive analysis... The projects to be executed are prioritized to form a scientific and reasonable execution sequence. Finally, the conflict resolution solution is determined according to the conflict handling rules. The prioritization results, solutions and the project center's schedule, resource status and process dependencies are integrated to generate a comprehensive project management adjustment plan. Based on this, a unified management mechanism is built with historical data as the foundation, intelligent analysis as the driving force and dynamic coordination as the goal. This systematically solves the problems of inaccurate deduplication, frequent conflicts, resource waste and control failure caused by manual reliance, fragmented processes and lack of data collaboration in the background technology. It realizes efficient, accurate and dynamic comprehensive management of the entire life cycle of information technology projects.

[0093] Please see Figure 3 , Figure 3 An embodiment diagram of an electronic device provided in accordance with the present invention. For example... Figure 3 As shown, this embodiment of the invention provides an electronic device 300, including a memory 310, a processor 320, and a computer program 311 stored in the memory 310 and executable on the processor 320. When the processor 320 executes the computer program 311, it performs the following steps: Based on the user-submitted preliminary project requirements data, intent is parsed to obtain the current project intent, and the current project intent is compared with the project intent in historical project data to obtain a project deduplication report; Based on the project plagiarism check report, a novelty analysis is performed to obtain the analysis results. If the analysis results indicate that the novelty meets the standards, then based on the pre-built management investment strategy form and the business architecture data and application architecture data corresponding to the current project, the compliance verification of the early requirements data of the current project is performed to obtain the verification results. If the verification result is passed, then based on the resource usage data, construction cycle data and technical architecture data of historical projects, conflict identification is performed on the project deduplication report to obtain the project conflict type and the associated historical project identifier. Then, based on the comprehensive score calculated for the current project and the projects to be executed, priority ranking is performed to obtain the ranking result. Based on the sorting results, project deduplication report, project conflict type and associated historical project identifier, and combined with the conflict handling rules data preset in the management investment strategy form, the conflict node solution is determined. Based on the sorting results, conflict node solutions, and the project schedule, resource usage, and management process dependencies of the project center, a comprehensive project management adjustment plan is obtained.

[0094] Please see Figure 4 , Figure 4 An embodiment diagram of a computer-readable storage medium provided in accordance with an embodiment of the present invention is shown. Figure 4 As shown, this embodiment provides a computer-readable storage medium 400 on which a computer program 311 is stored. When the computer program 311 is executed by a processor, it performs the following steps: Based on the user-submitted preliminary project requirements data, intent is parsed to obtain the current project intent, and the current project intent is compared with the project intent in historical project data to obtain a project deduplication report; Based on the project plagiarism check report, a novelty analysis is performed to obtain the analysis results. If the analysis results indicate that the novelty meets the standards, then based on the pre-built management investment strategy form and the business architecture data and application architecture data corresponding to the current project, the compliance verification of the early requirements data of the current project is performed to obtain the verification results. If the verification result is passed, then based on the resource usage data, construction cycle data and technical architecture data of historical projects, conflict identification is performed on the project deduplication report to obtain the project conflict type and the associated historical project identifier. Then, based on the comprehensive score calculated for the current project and the projects to be executed, priority ranking is performed to obtain the ranking result. Based on the sorting results, project deduplication report, project conflict type and associated historical project identifier, and combined with the conflict handling rules data preset in the management investment strategy form, the conflict node solution is determined. Based on the sorting results, conflict node solutions, and the project schedule, resource usage, and management process dependencies of the project center, a comprehensive project management adjustment plan is obtained.

[0095] On the other hand, the present invention also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer is able to execute the comprehensive information project management method based on big data analysis provided by the above methods, the method comprising: Based on the user-submitted preliminary project requirements data, intent is parsed to obtain the current project intent, and the current project intent is compared with the project intent in historical project data to obtain a project deduplication report; Based on the project plagiarism check report, a novelty analysis is performed to obtain the analysis results. If the analysis results indicate that the novelty meets the standards, then based on the pre-built management investment strategy form and the business architecture data and application architecture data corresponding to the current project, the compliance verification of the early requirements data of the current project is performed to obtain the verification results. If the verification result is passed, then based on the resource usage data, construction cycle data and technical architecture data of historical projects, conflict identification is performed on the project deduplication report to obtain the project conflict type and the associated historical project identifier. Then, based on the comprehensive score calculated for the current project and the projects to be executed, priority ranking is performed to obtain the ranking result. Based on the sorting results, project deduplication report, project conflict type and associated historical project identifier, and combined with the conflict handling rules data preset in the management investment strategy form, the conflict node solution is determined. Based on the sorting results, conflict node solutions, and the project schedule, resource usage, and management process dependencies of the project center, a comprehensive project management adjustment plan is obtained.

[0096] The system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0097] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., including several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods of various embodiments or some parts of embodiments.

[0098] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for comprehensive management of informationization projects based on big data analysis, characterized in that, The method comprises the following steps: Based on the project pre-requisite data submitted by the user, the intention analysis is performed to obtain the current project intention, and the current project intention is compared with the project intention in the historical project data to obtain a project duplication checking report; Based on the project duplication checking report, the novelty analysis is performed to obtain an analysis result, and if the analysis result is that the novelty meets the requirements, the pre-constructed management investment strategy form is combined with the business architecture data and the application architecture data corresponding to the current project to verify the compliance of the pre-requisite data of the current project, and a verification result is obtained; If the verification result is passed, the project duplication checking report is subjected to conflict identification based on the resource occupation data, construction period data and technical architecture data of the historical projects, a project conflict type and an associated historical project identifier are obtained, and the current project is subjected to priority ranking with the to-be-executed projects based on the comprehensive score calculated for the current project, and a ranking result is obtained; Based on the ranking result, the project duplication checking report, the project conflict type and the associated historical project identifier, and in combination with the pre-set conflict handling rule data in the management investment strategy form, a conflict node solution is determined; Based on the ranking result, the conflict node solution, the project schedule in the project center, the resource occupation situation and the management process dependency relationship, a project comprehensive management adjustment scheme is obtained.

2. The big data analysis-based informatization project integrated management method according to claim 1, characterized in that, The method of determining the conflict node solution based on the ranking result, the project duplication checking report, the project conflict type and the associated historical project identifier, and in combination with the pre-set conflict handling rule data in the management investment strategy form comprises the following steps: Based on the priority sequence number of the current project in the ranking result and the duplication degree identifier information in the project duplication checking report, a scheduling position of the current project in the to-be-executed project queue is obtained, and it is judged whether the current project is in a resource competition critical interval based on the scheduling position; If the scheduling position is in the resource competition critical interval, a plurality of historical project conflict handling context records are obtained by recording and extracting the resource dimension indicated by the project conflict type and the associated historical project identifier, and a historical handling strategy fragment matching the scheduling position of the current project is obtained by screening based on the conflict handling context records; Based on the conflict handling rule data in the management investment strategy form and the historical handling strategy fragment, a conflict handling rule group suitable for the current project is obtained; Based on the handling trajectory corresponding to each rule in the conflict handling rule group and the associated historical project identifier, a conflict resolution path topology structure with the current project as a root node is constructed; Based on the conflict resolution path topology structure, the conflict handling rule group and the management investment strategy form, the conflict node solution is determined. 3.The information-based project comprehensive management method based on big data analysis according to claim 2, characterized in that, The method of determining the conflict node solution based on the conflict resolution path topology structure, the conflict handling rule group and the management investment strategy form comprises the following steps: Based on the node in-degree and out-degree distribution characteristics in the conflict resolution path topology structure, a node group having branch selection ability in the topology structure is determined, and a key decision node is obtained by identifying the nodes having a decisive influence on the subsequent handling path based on the node group. Based on the out-edge connected with the key decision node and its corresponding conflict handling rule set, a plurality of complete handling paths from the current project to the historical project endpoint are determined, and based on the analysis of each complete handling path, a corresponding multi-branch handling scheme draft is obtained; Based on the technical components relied on by each scheme in the multi-branch handling scheme draft and the technical architecture data of the current project, the architecture adaptation state of each scheme is determined, and the handling schemes with architecture mutual exclusion are eliminated based on the architecture adaptation state to obtain candidate schemes; Based on the candidate schemes combined with the preset priority execution principle in the management investment strategy form, the execution priority of each candidate scheme is determined, and the candidate scheme ranked first is determined as the conflict node solution. 4.The information-based project comprehensive management method based on big data analysis according to claim 1, characterized in that, Based on the resource occupation data, construction period data and technical architecture data of the historical project, the project duplicate report is subjected to conflict identification to obtain the project conflict type and the associated historical project identifier, including: Based on the historical project identifier group matched with the intention of the current project in the project duplicate report, the corresponding historical project resource occupation data, historical project construction period data and historical project technical architecture data are extracted; Based on all the historical project resource occupation data in the historical project identifier group, a resource occupation topology structure group is constructed, and a topological isomorphism determination is performed based on the resource occupation topology structure group and the resource application topology structure in the project preliminary demand data to obtain a resource topology conflict identifier group; Based on the historical project construction period data corresponding to the resource topology conflict identifier group, a construction period time axis group is constructed, and a time axis intersection detection is performed based on the construction period time axis group and the planned construction period time axis of the current project to obtain a time overlap conflict identifier group; the planned construction period time axis of the current project is constructed based on the project construction start and end time node information contained in the project preliminary demand data; Based on the historical project technical architecture data corresponding to the time overlap conflict identifier group, a technical architecture component dependency graph group is constructed, and a component dependency path consistency comparison is performed based on the technical architecture component dependency graph group and the technical architecture component dependency graph of the current project to obtain a technical dependency conflict identifier group; the technical architecture component dependency graph of the current project is constructed with each technical component in the project preliminary demand data as a graph node and each dependency relationship as a directed edge; Based on the technical dependency conflict identifier group combined with the project preliminary demand data, the project conflict type and the associated historical project identifier are obtained. 5.The information-based project comprehensive management method based on big data analysis according to claim 4, characterized in that, Based on the technical dependency conflict identifier group combined with the project preliminary demand data, the project conflict type and the associated historical project identifier are obtained, including: Based on the technical dependency conflict identifier group, different types of conflicts are identified and analyzed to obtain a multi-dimensional conflict intersection identifier group, and based on each historical project identifier in the multi-dimensional conflict intersection identifier group, a conflict attribute combination in the resource topology, construction period and technical architecture dimensions is extracted to obtain a conflict feature triple. The conflict type mapping table is obtained by performing conflict mode clustering division based on the conflict feature triplets, and each historical project identifier is classified into a unique conflict type category based on the conflict type mapping table, so as to obtain a project conflict type assignment group; Based on the project conflict type assignment group, a conflict transmission chain is constructed, and based on the historical project identifiers associated with each conflict type in the conflict transmission chain, a conflict influence propagation path group is determined; Based on the semantic constraint matching between the conflict influence propagation path group and the business target description in the project pre-requisite requirement data, historical project identifiers that have irreconcilable constraints with the current project business target are screened out based on the semantic constraint matching result, so as to obtain the project conflict type and the associated historical project identifier. 6.The information-based project comprehensive management method based on big data analysis according to claim 5, characterized in that, The technical dependency conflict identification group is used to identify and analyze different types of conflicts, and a multi-dimensional conflict cross-identification group is obtained, including: The technical dependency conflict identification group is used to identify and analyze different types of conflicts, and a multi-dimensional conflict cross-identification group is obtained, including: The multi-dimensional analysis is performed for each conflict type, the analysis results of each dimension are integrated, and the multi-dimensional conflict cross-identification group is obtained; the multi-dimensions include time dimension, organization dimension, technology dimension and business dimension. 7.The information-based project comprehensive management method based on big data analysis according to claim 1, characterized in that, The project duplication checking report includes the similarity score of the current project and each historical project at the intention level, the overlapping dimension details and the difference point description.

8. The information-based project comprehensive management system based on big data analysis, characterized in that, The application is applied to the information technology project comprehensive management method based on big data analysis according to any one of claims 1 to 7. The information technology project comprehensive management system based on big data analysis includes: The intention analysis and duplication checking module is used to perform intention analysis based on the project pre-requisite requirement data submitted by the user, obtain the intention of the current project, compare the intention of the current project with the intention of the historical project in the historical project data, and obtain a project duplication checking report; The novelty analysis and compliance verification module is used to perform novelty analysis based on the project duplication checking report, obtain an analysis result, and if the analysis result is that the novelty is up to standard, perform compliance verification on the pre-requisite requirement data of the current project based on the pre-constructed management investment strategy form combined with the business architecture data and the application architecture data of the current project, and obtain a verification result; The conflict identification and priority sorting module is used to perform conflict identification on the project duplication checking report based on the resource occupation data, construction period data and technical architecture data of the historical project if the verification result is passed, obtain the project conflict type and the associated historical project identifier, and perform priority sorting on the project duplication checking report based on the comprehensive score calculated by the current project and the to-be-executed project, and obtain a sorting result; The conflict node solution generation module is used to determine a conflict node solution based on the sorting result, the project duplication checking report, the project conflict type and the associated historical project identifier, and the pre-set conflict handling rule data in the management investment strategy form; The scheme integration module is used to integrate the sorting result, the conflict node solution, the project progress plan, the resource occupation situation and the management process dependency relationship of the project center, and obtain a project comprehensive management adjustment scheme.

9. An electronic device, characterized by The memory is used to store the computer software program. ​ A processor is configured to read and execute the computer software program, and the processor, when executing the computer software program, implements the information-based project comprehensive management method based on big data analysis according to any one of claims 1 to 7.

10. A non-transitory computer readable storage medium, characterized in that, The storage medium stores a computer software program, and the computer software program, when executed by the processor, implements the information-based project comprehensive management method based on big data analysis according to any one of claims 1 to 7.

Images