221 results about "Project management system" patented technology

The invention discloses an informatization project management system based on big data analysis, which belongs to the field of big data and comprises a data acquisition module, a time sequence modeling module, a task coupling analysis module, a risk clustering identification module, a resource allocation prediction module and the like. The data acquisition module asynchronously and parallelly acquires structured and unstructured data and uniformly encodes the structured and unstructured data; the time sequence modeling module constructs a multi-dimensional time sequence based on an autoregressive residual network; the task coupling analysis module fuses the task trajectory and the dependency relationship to generate a task influence directed graph; the risk clustering identification module identifies risks through variational graph auto-encoder mapping; the resource allocation prediction module constructs a dynamic resource priority based on a graph attention mechanism; a progress deviation traceability module identifies a deviation causal chain; the knowledge graph decision-making module corrects resource priorities and path strategies in a cross-graph manner; and the project global control module dynamically adjusts key paths and resource configuration and performs closed-loop self-correction. The beneficial effect is that the intelligent level and the risk response capability of project management are improved.

An AI-powered agile project management system for automatic risk assessment and mitigation, including: a risk identification module configured to extract project data from agile project management tools, including but not limited to Jira, Trello, Asana, and Monday.com, and identify potential risks using machine learning and NLP; a risk analysis module configured to assign risk scores based on probability, impact, and severity using predictive analytics, where the module uses historical data, real-time project status, and external dependencies to determine the severity and impact of risks; a real-time monitoring module configured to continuously track project conditions, detect anomalies, and generate immediate notifications via email, mobile apps, or messaging platforms when high-risk events are identified; a risk mitigation module configured to dynamically recommend and execute proactive corrective actions such as task reassignment, resource optimization, schedule adjustments, and implementation of alternative strategies using AI-driven decision-making, where the actions can be automated through predefined workflows or manually adjusted based on AI recommendations; an AI-driven task prioritization module configured to dynamically prioritize tasks based on risk factors, project deadlines, and team workload distribution; an integration module configured to ensure seamless compatibility with existing Agile project management frameworks through API-based synchronization; a learning and continuous improvement module configured to refine risk prediction models over time using machine learning and historical risk mitigation results, with AI-driven models continuously updating risk assessment mechanisms based on evolving project conditions, industry-specific risk factors, and historical performance metrics; a compliance and audit reporting module configured to automatically generate risk reports, audit logs, and compliance checklists; a customizable risk assessment configuration module configured to allow project managers to define custom risk parameters, probability thresholds, and mitigation preferences; an interactive dashboard module configured to visualize data in real time, including risk trends, effectiveness of remedial actions, and analysis of project progress; and a scalability feature configured to be used in industries such as IT, healthcare, finance, construction, and manufacturing.

The invention provides an intelligent project management system based on supervision integration, and the system employs a cloud platform for deployment, and comprises a project management module which is used for task management, progress tracking and document sharing, so as to achieve the planning, starting, execution, monitoring and ending of a whole life cycle of a project; the data acquisition and integration module is used for collecting project data in real time and performing integration processing; the risk assessment and early warning module is used for performing risk assessment on the project data and giving out early warning when the risk exceeds a preset threshold value; the intelligent decision support module is used for providing decision suggestions for a project manager based on the data analysis result; and the visual display module is used for visually displaying information such as a project state, progress, cost and quality in forms such as charts and reports. According to the system, through an integrated management platform and an intelligent analysis tool, real-time monitoring, risk assessment, resource optimization and decision support of the full life cycle of a project are realized, so that the project management efficiency is improved, and the project risk is reduced.

The invention relates to the technical field of data processing, and discloses a standardized document automatic generation method for software development, which comprises the following steps: establishing a document template library which comprises a plurality of document templates formulated according to software engineering standards; the method comprises the following steps: acquiring project data based on a project management system, wherein the project data comprises structured project data and unstructured project data; according to a preset rule engine, automatically filling the project data into the document template to generate a standardized project document; and performing version control and dynamic updating on the standardized project document. According to the method, the document generation efficiency and consistency are improved, redundancy and errors in the manual processing process are avoided, and transparent and standardized management of the whole process of project data is achieved.

The invention relates to the technical field of construction project management, in particular to a construction project management system based on cloud computing, which comprises a construction path optimization module, a construction state analysis module, a construction environment monitoring module, a progress plan adjustment module and a green construction optimization module. According to the method, through combination of construction task resource distribution and three-dimensional space information, resource path distribution logic is optimized, material consumption, equipment operation states and key process deviation data are utilized, accurate positioning and prediction of construction dynamic problems are realized, construction interruption is reduced, and equipment and personnel distribution characteristics are extracted based on field image data, so that construction efficiency is improved. The equipment arrangement deviation degree and the potential safety hazard superposition value are quantified, the safety and efficiency of a construction site are improved, and the utilization rate of green construction resources is improved by dynamically adjusting the process time and the resource utilization rate, optimizing the relation between task nodes and factors, improving the flexibility and the response capability of a construction plan and conducting partition modeling energy consumption data and multi-constraint optimization.

The invention discloses a bank system research and development project management system, and the system comprises an intelligent management platform which generates a compliance check list and a difference report through the real-time butt joint of a supervision database; the risk prediction module is used for predicting risk levels such as research and development cycle delay and resource hyperbranched, triggering early warning and suggesting a deployment scheme; the block chain evidence storage and tracing module is used for storing the hash value and the operation record of the key node document in a chaining manner, and solidifying a timestamp and a person in charge; the task collaboration module is used for analyzing a demand document by using NLP, automatically disassembling the demand document into an executable task tree, analyzing manpower and equipment conflicts through a resource occupation graph, and intelligently generating a deployment scheme; and the security control module is used for implementing hierarchical authority based on role and data sensitivity, and sensitive operation needs dual verification of biometric authentication and dynamic token to prevent unauthorized access. The system is high in risk resistance, high in overall research and development efficiency and fast in data management and auditing, and can meet the requirements in the research and development process of a bank system.

The invention discloses a project management system and method based on a generative adversarial network. The system comprises a data acquisition unit, a feature extraction unit, a progress prediction unit and a scheme generation unit. Wherein the feature extraction unit is used for respectively extracting time sequence features and space features by adopting a long-short term memory network and a multi-head image attention network; the progress prediction unit generates a prediction sequence through a generator based on a generative adversarial network architecture, and evaluates the rationality of the prediction sequence through a discriminator; the scheme generation unit generates a progress adjustment scheme based on key path analysis, resource optimization and a buffer time allocation method; according to the invention, the accuracy and reliability of project progress prediction can be effectively improved, and a scientific basis is provided for project management decision.

The invention relates to the field of intelligent management of water conservancy projects, and provides an engineering project management system and method based on big data analysis. According to the method, historical hydrological data including specific indexes such as water level, reservoir inflow and reservoir outflow and historical meteorological data including specific indexes such as rainfall, evaporation capacity and air temperature of a target management reservoir are comprehensively analyzed by adopting a data analysis technology based on deep learning; and a reservoir dispatching operation scheme is generated based on the features obtained through comprehensive analysis. In this way, the problems that a traditional decision-making mode lacks data support and scientific analysis is insufficient can be solved, and the scientificity and rationality of reservoir management decision-making can be improved.

The invention relates to the technical field of medical information management, in particular to an intelligent hospital scientific research project management system, which comprises a project information input and editing module for inputting and editing basic information of a scientific research project, and an approval process management module for approving a scientific research project approval application according to a preset approval process, the task distribution and management module is used for performing task decomposition and distribution on the approved scientific research project, the progress tracking and monitoring module is used for collecting and displaying the overall progress of the scientific research project in real time, the fund management module is used for budgeting the fund of the scientific research project, and the result acceptance and management module is used for checking and managing the fund of the scientific research project. The system is used for organizing acceptance and warehousing management of scientific research project achievements. According to the hospital scientific research project management system, integrated management is adopted, delay and repeated work of information transmission among departments in a traditional management mode are avoided, the project can be efficiently promoted, the project period is greatly shortened, and the overall management efficiency of hospital scientific research projects is improved.

The invention discloses a building engineering management system and management method, and relates to the technical field of construction dust risk management. Dust monitoring points are arranged in a construction site, dust related parameters of a plurality of dust monitoring areas are monitored in real time, a diffusion data set and a mechanical operation distribution data set are combined, and construction dust risk management is performed. And carrying out deep calculation on the data by utilizing a neural network technology, and accurately obtaining the ground dust raising intensity, the mechanical operation dust raising index and the material storage dust raising diffusion ratio of each dust raising monitoring area. And performing association to obtain a regional dust raising comprehensive index Yczsi of the ith dust raising monitoring region, and then performing evaluation to automatically generate a risk grading result. According to the intelligent evaluation based on the data, errors caused by manual estimation are avoided. And according to the grading result, the system can automatically adjust dust raising control measures, such as watering, dust screen setting or construction plan adjustment, so that reasonable control measures are adopted in different risk grade areas, and the generation of dust raising pollution is further reduced.

The invention belongs to the technical field of computer-aided project management, and discloses an electric power engineering design project management system and method, and the system comprises a data integration and processing module, a multilayer dynamic knowledge graph data storage library, a graph-based automatic compliance check engine, and a graph neural network-based predictive risk engine. And an active design change impact analysis module. According to the method, a unified and intelligent project data core is constructed, heterogeneous data sources such as design files and law and regulation texts are integrated in a multi-layer dynamic knowledge graph, automatic compliance review is realized by utilizing graph query, data-driven risk prediction is realized by utilizing a graph neural network GNN, and the risk prediction efficiency is improved. And the linkage influence of design change can be simulated and quantitatively evaluated. According to the method, the problems of data islanding, passive compliance examination, subjective risk management, difficulty in change analysis and the like in the prior art are solved, and the management efficiency, accuracy and initiative of the electric power engineering design project can be remarkably improved.

The invention relates to the technical field of water conservancy data processing, in particular to a GIS-based water conservancy project management system, which comprises a non-stationary data decomposition module, a nested autoregression modeling module, a space-time dynamic reconstruction module, a risk quantitative mapping module and a risk decision optimization module. According to the method, long-term changes and short-term fluctuations are quantified and synthesized term by term through hydrological time series data in trend fitting and fluctuation amplitude extraction, the precision and timeliness of time series prediction are improved, dynamic integration of data of multiple monitoring points is achieved in combination with geographic information matching and spatial difference value distribution analysis, and the accuracy and timeliness of time series prediction are improved. According to the method, the spatial distribution of water resources is accurately predicted, the correlation degree between regions is quantified, risk index quantification is combined with a spatial interpolation technology, so that risk region division is more detailed, the pertinence of emergency management is optimized, and the scientificity and execution efficiency of risk decision are further improved based on scheduling data analysis and influence factor quantification.

An AI-driven project management system to optimize resource allocation and project schedules, including: a) a data entry module (101) configured to capture and process historical and real-time project data, including resource availability, task dependencies, and staff capacity; (b) a predictive analytics engine (102) that uses machine learning algorithms to analyse project data and generate predictive insights into potential risks, bottlenecks and inefficiencies; c) an intelligent planning module (103) that uses reinforcement learning and constraint optimization techniques to dynamically allocate resources and adjust schedules in response to changing project conditions; (d) a risk assessment module (104) that integrates natural language processing (NLP) and structured data analysis to identify emerging project risks and recommend risk mitigation strategies; and (e) a continuous learning framework(105) that refines AI models over time based on project results, ensuring better decision-making accuracy and adaptability for future projects.

The invention relates to the technical field of modularized laboratory project management, and discloses a modularization-based laboratory project management method, which comprises the following steps: S1, system architecture design: adopting a micro-service distributed architecture, and cooperatively working through a plurality of business modules; s2, module management and project creation; the invention also provides a laboratory project management system based on modularization, which comprises a project management engine module, an intelligent key node reminding system, a sample full life cycle tracking management module and a multi-party collaborative feedback management module, the project management engine module comprises three core business modules, namely, a project management module, a sample management module and a contract management module, standardized management and efficient operation of laboratory projects are achieved through a project module engine, an intelligent node reminding mechanism and a full-process tracking algorithm, the project management efficiency can be remarkably improved, and the project management efficiency is improved. And the time cost of a project preparation stage is saved.

The invention discloses a Web3D-based game development data driving system, and relates to the technical field of game development, the system comprises a user editing system, a project management system, a data management system and a rendering system; the user editing system is used for providing a visual editing interface, and the visual editing interface is used for a user to create game items and perform game scene editing on the created game items; the project management system is used for synchronizing change operation generated by game project creation or game scene editing performed by at least one user through the user editing system to the data management system in real time; the data management system is used for carrying out data change based on a data persistence and consistency guarantee mechanism of the graph database according to each change operation; and the rendering system is used for performing real-time 3D rendering on the scene data in the data change and feeding back a 3D rendering result to the user editing system through the project management system. The game opening efficiency can be improved.

The invention provides a task management method and a project management system for a scientific research platform, and relates to the technical field of data processing, and the method comprises the steps: obtaining a to-be-allocated task in the scientific research platform; splitting the to-be-allocated task into a plurality of sub-tasks according to an execution time sequence; the planned completion time of each subtask is distributed; extracting a feature vector of each subtask; obtaining the feature vector of each person; according to the feature vector of each sub-task and the feature vector of each person, distributing a plurality of execution candidates for each sub-task in combination with a collaborative filtering algorithm; determining a final executor of each sub-task from the execution candidates through a multi-objective optimization algorithm by taking minimization of task completion time and minimization of task failure factors as targets; in the execution process, the task execution progress is monitored according to the planned completion time. The task allocation efficiency can be improved, the task allocation personnel rationality is improved, and the scientific research task completion efficiency is improved.

The invention discloses a project management system based on a SpringBoot micro-service architecture. The project management system comprises an application layer, a support layer and a basic platform, the application layer comprises a user portal function module, and the user portal function module comprises a user login module used for providing a login interface; the achievement consulting module is used for supporting a user to retrieve project achievements in the system through keywords, displaying a related achievement list and providing excellent achievement displaying and downloading functions; the project filling and reporting module is used for supporting a user to fill basic information of a project or upload an attachment to form a project manuscript on line based on a template; the project review module is used for supporting initial review, expert review, summarized review, file uploading and batch export of project manuscripts; the support layer is used for providing a project filling and project review circulation process and a data management function, and the basic platform is used for providing an operation environment and hardware support. According to the invention, a project management solution which is easy to operate and efficient and stable to operate can be provided for a user.

The invention relates to the technical field of management, in particular to a BIM-based project management method and system, and the BIM-based project management system comprises a plan simulation module, a dynamic updating module, a progress comparison module, a reason analysis module, an automatic scheduling module and a resource management module. The plan simulation module generates a building construction 4D simulation video; the dynamic updating module collects progress data of a construction site in real time and generates an actual construction progress; the progress comparison module compares the actual construction progress with the construction reference progress plan, and finds out the specific situation of the backward construction progress if the backward progress is found; the reason analysis module analyzes the root reason of the backward construction progress according to the specific situation of the backward construction progress; the automatic scheduling module automatically adjusts the sequence and time arrangement of construction tasks according to the root cause of the backward construction progress and generates resource allocation information, and the resource management module allocates resources again according to the resource allocation information.

The invention relates to the technical field of construction management, in particular to a water conservancy construction project management system based on data analysis, and the system comprises a water flow monitoring module which collects water flow data in a construction area in real time through a sensor; the meteorological data acquisition module is used for acquiring surrounding future precipitation, performing correlation analysis on the future precipitation and the water flow data and predicting a future water level change trend; the construction progress management unit divides the construction progress into a plurality of construction stages, and the construction stages are uploaded by site construction managers in real time; the data analysis module is used for identifying the influence of the water flow change trend on the specific construction stage; and the self-adaptive water flow regulation module is used for formulating water flow management measures according to an analysis result of the correlation influence model. According to the method, visual quantitative indexes are provided for construction managers, and resource allocation and construction scheduling are optimized, so that the construction management efficiency is remarkably improved, and the occurrence probability of progress delay and safety accidents is reduced.

The invention discloses an advertisement design project management system, which relates to the technical field of project management, and comprises an information acquisition unit, the information acquisition unit is used for acquiring operation information and feedback information and sending the operation information to an information analysis unit, and the information analysis unit acquires the operation information and extracts a browsing keyword set based on the operation information; the method comprises the following steps: respectively calculating comprehensive demand indexes of browsing keywords and dividing pushing grades of the keywords, acquiring user information by an advertisement distribution unit, carrying out association matching on the user information and a coincident keyword set, and pushing associated keywords to a matched pushing user set, acquiring feedback information by a feedback analysis unit, calculating a comprehensive feedback coefficient, and sending the comprehensive feedback coefficient to the advertisement distribution unit. And a putting adjustment signal is generated. According to the method, by dividing the pushing levels of the keywords, the advertisement pushing accuracy is improved, the project management efficiency is improved, the advertisement putting effect is optimized in real time through feedback adjustment, the advertisement cost can be effectively reduced, and the rate of return on investment is improved.

The invention relates to the technical field of intelligent project management, in particular to a real-time data intelligent association calculation method applied to a project management system, and the method comprises the following steps: constructing a project management knowledge graph, and carrying out the structural storage of historical projects; when the new software development project is started, extracting feature information of the new project; synthesizing the graph structure similarity and the semantic similarity to determine a historical software development project most similar to the new project; generating an initial association rule set according to a matching result; adopting a transfer learning technology to generate a self-adaptive association rule suitable for a new project; and adjusting the association rule according to the change of the real-time monitoring data, and reallocating resources or adjusting the task dependency relationship. According to the method, association rules, risk cases, task dependency relationships and resource allocation strategies of historical projects are stored in a structured manner by constructing the project management knowledge graph, and hidden experience in unstructured data is mined by using a natural language processing technology, so that repeated occurrence of similar problems is avoided.

The invention relates to the technical field of artificial intelligence and engineering project management, provides a full-cycle engineering project management system and method, and aims to solve the problems of data fragmentation, decision-making dependence on manpower and low execution collaboration efficiency in traditional engineering project management. The system comprises a data layer, a processing layer and an application layer. The data layer integrates a historical change data warehouse, dynamic market data, a supply chain collaborative database and BIM model full life cycle management, and multi-source heterogeneous data association storage is achieved. The processing layer extracts changed text key information through an NLP semantic analysis module, judges the priority, outputs a quantitative decision basis in combination with an intelligent decision support module (risk prediction, multi-source data fusion and BIM simulation), and realizes task optimal allocation and progress monitoring through an automatic execution module; and the application layer provides an interactive interface to support full-process visual collaboration. The method comprises the four stages of change request submission, NLP semantic analysis, approval decision making and automatic execution, and closed-loop management is formed.

The invention discloses an intelligent building engineering management system based on a BIM platform, and relates to the technical field of building engineering management, and the system comprises a BIM model database, a participant interface module, a real-time synchronization module, an automatic notification module, an authority management module and a block chain recording module. According to the intelligent building engineering management system based on the BIM platform, computing resources and storage capacity are flexibly adjusted according to project requirements, and the requirements of projects of different scales are met; the block chain recording module supports a multi-chain synchronization function, and different participants can record on independent chains; therefore, the security of the data is ensured, the expandability of the building engineering management system is improved, and the individual requirements of different participants are met; the automatic notification module adopts a plurality of channel notification modes, and supports a user-defined reminding mode and priority setting of a participant; therefore, information transmission is more flexible and diversified, and working habits and requirements of different participants are met.

The work breakdown structure (WBS) table in a computerized project management system is modified to include individual columns for each of the resources that is used on a project to produce a scope-resource matrix within the WBS table. The matrix is created when users add each resource directly to a project's WBS table. The users assign the resources to individual tasks and subtasks in the project by adding the allocation level directly the matrix at the intersection of the resource and each task to which the resource is assigned. Also, the computerized project management system automatically reformats selected task rows in the WBS table from their original data field format to a composite operator-data field format when a user adds subtasks to the selected task row. The computerized project management system also allows users to group columns in the WBS table, and the grouped columns can be shown or hidden.

The invention discloses a dynamic science popularization project management system based on interdisciplinary data fusion. According to the system, a multi-source data warehouse is constructed, astronomy, geography, programming behaviors and evaluation data semantics are aligned into a knowledge graph, and a personalized project type exploration task is generated through semantic path search in combination with a student cognitive state graph; the multi-agent reinforcement learning scheduling engine allocates resources in real time, optimizes task paths, fuses behavior modeling and a fuzzy evaluation model in task execution to generate cognitive feedback and advanced capability evaluation, and realizes automatic task generation, intelligent scheduling and closed-loop evaluation in popular science teaching.

Embodiments of the present disclosure disclose an information processing method, and an electronic device. A specific implementation of the method includes: establishing, in a project management system, a dependency relationship between a first sub-object of a first work item and a second sub-object of a second work item based on a dependency configuration operation; and displaying, in a first work item display interface, dependency relationship information indicating the dependency relationship. Therefore, a new information processing manner is provided. The dependency relationship is used to represent that opening or completion of the first sub-object depends on a status of the second sub-object.

The invention relates to the field of construction engineering project management, in particular to an infrastructure engineering project management system based on big data. The method comprises the steps of obtaining multi-modal engineering project data in a system, performing space-time alignment on the multi-modal engineering project data, processing abnormal values in the aligned data to obtain complete engineering project data, performing multi-modal fusion on the complete engineering project data, and constructing a feature library of the fused engineering project data. And establishing a ResNet-Transform risk prediction model, optimizing hyper-parameters of the model by using an IWOA improved whale optimization algorithm, inputting the feature engineering project data into the target risk prediction model for prediction, and performing construction planning based on the construction engineering project state. The problem of data islands is solved, a complete data set covering engineering total elements is formed, the system can automatically trigger a hierarchical response strategy, and closed-loop management from risk identification to planning adjustment is achieved.

The present application relates to the field of enterprise management, and provides a research and development project data processing method and a research and development project management system. A first research and development corresponding relation between a candidate research and development project and a candidate research and development expense is inputted into an expense association module; then on the basis of the first research and development corresponding relation, a candidate research and development expense corresponding to a target research and development project, unit man-hour information corresponding to the target research and development project, and total man-hour information corresponding to the unit man-hour information are obtained; subsequently, the ratio of the unit man-hour information to the total man-hour information is determined, and a target research and development expense is determined on the basis of the ratio and the candidate research and development expense; and finally, the target research and development expense is stored in a newly-built data table. Thus, the association between an expense management module and a research and development management module is improved, the accuracy of measuring a research and development project expense and the traceability of underlying data between modules are improved at the same time, and the working efficiency of enterprise management is improved.

Disclosed is a project management system (100) comprising a processor (102) configured to execute project management functions based on project data. The system includes a remote server (104) operatively connected to the processor (102) for the storage and retrieval of the project data. A storage device (106) is operatively connected to the processor and stores a plurality of software modules. Each module, when executed by the processor (102) is configured to perform specific project management functions using the project data.

The invention provides an employee work assessment recommendation method and system based on a collaborative filtering algorithm, and relates to the technical field of employee work assessment, and the method comprises the steps: extracting a task dependency relationship and time consumption data from a project management system, and constructing an employee task dependency graph; secondly, collecting and analyzing work interaction information containing document operation and task marking features, and identifying task switching critical points to generate quantitative indexes; constructing a similar employee group and extracting an efficient working mode by means of a collaborative filtering algorithm after establishing an evaluation data set through space-time alignment of the two; by taking the task dependency graph as an environment state and the efficient mode as a reference, generating a task sequence optimization scheme by using a reinforcement learning model; according to the scheme, the staff group composition is adjusted according to the scheme execution effect, the optimization model is fed back, finally, a comprehensive evaluation result is generated based on the scheme and actual task sequence matching degree and the quantitative index stability, the task sequence optimization and physiological state adjustment ability can be accurately evaluated, and the work assessment scientificity and the task execution efficiency are improved.