159 results about "Project execution" patented technology

The invention discloses a task scheduling optimization and feedback control method and system based on a causal graph structure, and relates to the technical field of task scheduling, and the method comprises the steps: integrating multi-source information, identifying an entity, constructing a directed edge connection entity, calculating an edge weight, and forming a task causal graph; performing deep analysis on the causal graph, and identifying risk nodes and propagation paths thereof in the current project; combining the edge weight and the node attribute, quantifying the risk propagation possibility and influence range, and generating a risk thermodynamic diagram; on the basis of the identified risk nodes and propagation paths thereof, mining controllable variables in a task scheduling process, constructing a scheduling optimization objective function, searching a scheduling solution space under constraint conditions by using a search method, and evaluating the influence of different strategies on a task network through multiple rounds of simulation, so as to improve the task scheduling efficiency. A current optimal task adjustment strategy is screened out and practically applied; and collecting data generated in a project execution process, and updating the causal diagram. The method is suitable for intelligent scheduling and fine management scenes of projects.

The invention discloses a project execution risk assessment system and method based on data mining, and relates to the technical field of project execution risk assessment, and the method specifically comprises the following steps: obtaining comprehensive data information related to project execution, and storing the comprehensive data information after obtaining; analyzing the stored comprehensive data information, evaluating an accumulated risk of dependency of each task chain in a project execution process, classifying each task chain in the project according to an evaluation result, identifying high-risk, medium-risk and low-risk task chains, and generating a corresponding risk evaluation report; according to the risk assessment report, advising a manager to take corresponding risk mitigation measures for task chains of different risk levels; and updating comprehensive data information in real time, periodically recalculating an accumulated risk assessment coefficient, and dynamically adjusting a risk assessment result. According to the method, the problem of accumulative risk assessment of a complex dependent task chain is solved, and the effects of accurate classification management and dynamic risk adjustment are achieved.

The invention relates to the technical field of information data processing, in particular to a building engineering project data processing system, which comprises a resource demand analysis module, an engineering project-based human resource management and material demand plan, man-hour record and material inventory data collection module, timetable and resource use record arrangement module, resource utilization rate and gap calculation module and a data processing module, a resource status report is generated, and a resource supply status and potential shortage are determined based on the resource status report. According to the invention, through comprehensive data collection and dynamic analysis, the resource management efficiency of the construction engineering project is improved. Updating resource utilization rate and gap information in real time allows for fast and accurate response to resource changes, reducing resource waste and project delay risks. The resource allocation efficiency and the cost simulation ensure that the resource use reaches the optimal economic benefit, and meanwhile, the capability of the project for adapting to uncertain factors is improved. Time conflicts in resource allocation are reduced through risk assessment, and the continuity of project execution is optimized.

The invention discloses a human resource information management system and method based on big data, and relates to the technical field of human resources, and the system comprises a project demand analysis module which is used for extracting a skill list required by new project post personnel, determining task complexity, and generating skill parameter requirements; the employee screening module is used for obtaining the basic information of all the employees in service and dividing the employees in service into two types of crowds, one type is the crowd meeting the new project employment, and the other type is the crowd not meeting the new project employment, through big data analysis and multi-dimensional evaluation, accurate matching of the project demand and the employee ability is achieved, and the work efficiency is improved. Project execution quality and efficiency are improved, enterprise internal human resource potential is fully excavated, personnel can be reasonably allocated, and waste and idleness of human resources can be avoided.

The embodiment of the invention provides a project execution path planning method and device based on multi-path resource detection and multi-strategy decision, and an electronic product, and the method comprises the steps: analyzing a description file of a target project, so as to recognize function modules defined in the target project from the description file, and matching a target task of each function module; generating a task dependency path tree for the target task, and determining a minimum resource demand when the target project is executed; allocating task initialization configuration for each target task based on the minimum resource demand so as to determine a task execution path; adjusting the task initial configuration and / or the task execution path based on a set plan execution limiting condition until the task initial configuration is matched with a plurality of set planning strategy configurations; and generating a project execution path plan based on the resource configuration and the task execution path during matching.

According an embodiment of the present invention, a system processes requests to perform projects. The system comprises one or more memories, and at least one processor coupled to the one or more memories. The at least one processor processes a request in a natural language to perform a project via a hierarchy of machine learning agents. One or more machine learning agents of a management layer of the hierarchy determine and assign tasks for the project to one or more machine learning agents of an operation layer of the hierarchy based on the request. The at least one processor performs the assigned tasks by the one or more machine learning agents of the operation layer to perform the project. Embodiments of the present invention further include a method and computer program product for processing requests to perform projects in substantially the same manner described above.

The invention provides an engineering project report generation method, device and equipment based on an AI large model, and the method comprises the steps: receiving a prompt word inputted by a user, and generating a work report template according to the prompt word; extracting related contents of the work report template from a knowledge base by using a large language model, and filling each module in the work report template with the related contents to obtain each report module; checking and adjusting each report module by utilizing the large language model to obtain each adjusted report module; and integrating the adjusted report modules by using the large language model to generate a target work report. According to the method, the document files of the project execution condition are integrated and the work report required by the user is generated by utilizing the large language model and the knowledge base, so that the efficiency of generating the work report is improved, and meanwhile, the accuracy of the work report is improved.

The invention relates to the technical field of artificial intelligence, and particularly provides a project whole-process data tracking processing method and system, and the method comprises the steps: obtaining project planning data, extracting the relation between task information and tasks from the project planning data through a pre-training language model, and constructing a knowledge graph based on the relation between the task information and the tasks; acquiring project execution data from a plurality of data sources, and identifying task execution information from the project execution data; predicting a task progress based on a data sequence formed by all task execution information of the task, and adding state attributes for corresponding nodes of the knowledge graph based on the task progress; and analyzing an abnormal condition of a task execution state based on the knowledge graph after the state attribute is updated, analyzing an abnormal factor based on the project execution data, and generating a processing scheme for the abnormal factor by utilizing a pre-constructed knowledge base. According to the invention, the refined and intelligent level of project management is improved.

The invention provides a method, a device, equipment and a medium for generating an engineering project management digital model, and the method comprises the steps: collecting original data related to engineering project features, carrying out the preprocessing, forming a standardized project data set, constructing a space-time reference frame based on the data set, fusing a multi-dimensional feature tensor of multiple engineering features, and carrying out the construction of a space-time reference frame. The method comprises the steps of generating a project progress node and an integrated feature tensor, fusing the project progress node and the integrated feature tensor to generate a multi-source association graph containing entity relationships and feature semantics, generating a verified engineering project management digital model according to the project progress node, the integrated feature tensor and the association graph, and dynamically updating and optimizing the model in response to change data in project execution. According to the method, the problems of data dispersion, lack of association and static stiffness of the model in a traditional method are solved, automatic construction and dynamic evolution from multi-source heterogeneous data to an intelligent decision-making model are realized, and the accuracy, real-time performance and intelligent level of project management are remarkably improved.

The invention provides an inertial sensing range and sensitivity adjusting method, which belongs to the technical field of parameter adjustment, and comprises the following steps: after an item opening instruction is obtained, obtaining basic information of a moving body, and calling an adaptive sensing range according to the basic information; different detection nodes are set in the whole process before a project is started, the feedback degree of a moving body is recorded in sequence when execution is carried out to each node, values of corresponding positions of an internal curve are increased or decreased according to the feedback degree, and corresponding sensitivity is dynamically set according to the internal curve. The feedback speed and external performance of the moving body are judged in the project execution process, and the follow-up content and links of the project are adjusted in combination with the action model library till the project is completed or closed. The inertial sensing range and sensitivity adjusting method provided by the invention can carry out specific dynamic adjustment according to the state of the moving body and the actual situation, has strong pertinence and ensures smooth completion of a project.

The invention relates to the technical field of project management, and particularly discloses a project management method and system based on an AI large model technology, and the method comprises the steps: collecting multi-dimensional project execution data, carrying out the data cleaning and feature coupling analysis of the multi-dimensional project execution data, and generating a normalized project feature tensor; inputting the task delay risk into a pre-trained time sequence prediction large model, and outputting a task delay risk probability distribution matrix; carrying out risk level label mapping based on the task delay risk probability distribution matrix, and generating a multi-level risk early warning signal; and in response to the risk event exceeding the preset threshold in the multi-level risk early warning signal, a resource redistribution scheme is generated, and a project manager not only can monitor the project progress in real time, but also can quickly adjust resource configuration when the risk occurs, thereby realizing dynamic management. The intelligent project management mode based on data driving not only improves transparency and controllability of the project, but also provides powerful technical support for successful implementation of the project.

The invention relates to the technical field of project process management, in particular to an engineering design project process management system and method.The engineering design project process management system comprises a key path recognition module, a risk assessment module and a dynamic adjustment module, and the key path recognition module is used for recognizing key path tasks of a project; the risk assessment module carries out risk assessment on each key path task and calculates the initial buffer time of each key path task; the dynamic adjustment module is used for adjusting the initial buffer time of the key path task according to the actual completion time of the key path task in the project execution process; and the saved buffer time is allocated to a critical path task for a high-risk task in risk assessment for adjustment.

The invention discloses a project execution result determination method and device, equipment and a computer medium. The method comprises the steps that multiple to-be-verified links of a target project are acquired; and determining a target completion result of the target project according to the link identifier of each link to be verified in the plurality of links to be verified. The method can play a role in improving the determination efficiency of the target completion result of the target project.

The invention discloses a project combination adjusting method, and particularly relates to a project combination adjusting method and device based on dynamic risks and electronic equipment. The method comprises the following steps: acquiring support degree information corresponding to an existing project combination at a moment t-1, and acquiring risk influence information at a moment t; updating the support degree information based on the risk influence information to obtain updated support degree information at the moment t; judging whether the existing project combination meets a preset constraint condition or not based on the updated support degree information at the moment t; under the condition that the existing project combination does not meet the preset constraint condition, the adjustment cost corresponding to each project adjustment scheme is calculated, and the project adjustment scheme comprises an adjustment strategy executed by each existing project; and adjusting the existing project combination based on the project adjustment scheme with the lowest adjustment cost to obtain an updated project combination at the moment t. According to the method, the project combination can be dynamically adjusted according to the risk impact, and efficient allocation of resources is realized.

The invention relates to the technical field of building engineering management, and discloses a multi-dimensional building subpackage provider evaluation method based on a machine learning algorithm, and the method comprises the following steps: collecting data; the method comprises the following steps: cleaning and standardizing collected original data in two dimensions of basic information and project execution information, and dividing the data in the two dimensions into two data sets; clustering sample data of one data set in two dimensions by using a K-means clustering algorithm, performing label labeling through manual labeling, and respectively generating data training sets; respectively training the two KNN models through the data training set after label labeling, and selecting respective optimal neighbor quantity values through cross validation; and performing classification prediction on the second basic data set and the second item execution data set by using the two trained KNN models, and calculating a comprehensive score of each subpackage provider based on a prediction result. The accuracy and the reliability of an evaluation result can be remarkably improved.

A large language model (LLM)-based method includes receiving, from a user terminal, a transition command to a project-type chat window and information regarding a project execution period; in response to receipt of the transition command, determining a context retention period for the project-type chat window using the information regarding the project execution period; automatically generating a prompt for generating, using the LLM, a response to a query input from the user terminal, wherein the prompt is automatically generated to include the second query and information on one of a plurality of topics corresponding to the project-type chat window designated in the second query, and the response is generated in consideration of contexts of a plurality of conversations during the context retention period of the project-type chat window; and transmitting the response received from the LLM using the prompt, as a response to the second query, to the user terminal.

The invention relates to the technical field of enterprise resource management, in particular to an enterprise management optimization method and system based on big data, and the method comprises the following steps: capturing data of employee skills, a project execution process and customer interaction according to enterprise resource planning in an enterprise, analyzing the captured data, and carrying out the multi-dimensional information classification processing; and constructing an enterprise resource comprehensive data set. According to the method, the flow and utilization efficiency of the resources is improved by establishing the graphic database to integrate the enterprise resources and converting the data elements into the network nodes and the connecting edges, and the resource flow and utilization efficiency is improved by identifying and analyzing the association strength of the nodes and the weights of the edges in the resource network. Through detailed flow path analysis, an enterprise can formulate a scientific resource allocation strategy according to market requirements and current resource situations, resource allocation and use are optimized after dynamic resource allocation is implemented, the strategy is adjusted in time by comparing and analyzing resource efficiency and cost effectiveness before and after optimization, and the market response speed and competitiveness of the enterprise are remarkably improved.

The invention relates to a product full life cycle management method. The method comprises the following steps: constructing a collaborative project management platform; a product full-life-cycle management platform is constructed for overall management of various projects, military product models, temporary tasks and technology pre-research projects are overall managed in the longitudinal and transverse directions, project management methods, tools and knowledge are fully utilized, and integrated management of all elements and the whole process of various projects is achieved; through standardization, process and visualization of a project execution process, the cooperative capability of the project is improved, comprehensive system integration is realized, and deep business fusion and accumulation and reuse of project experience and knowledge are realized; according to the invention, by establishing a product full-life-cycle management collaborative research and development platform, the combination of product research and development, process design and production and manufacturing is realized, and a digital design and process integrated application mode is formed. And meanwhile, standard, unified and safe management of product research and development data is realized, and integration with an external application system is supported. And basic data research and development support is provided for an external system.

The invention discloses a project full life cycle management system based on a design industry, and belongs to the technical field of design project management, and in the project full life cycle management system, a project management module ensures ordered starting and execution of design projects through project planning and resource management. The project planning sub-module helps a project manager and a team to clarify a project target, a range, a milestone and a key deliverable, thereby laying a foundation for project success. The resource management sub-module ensures reasonable utilization and optimal configuration of resources in a project execution process through effective allocation of resources such as manpower, materials, equipment and funds, so that the project execution efficiency is improved, and the risks of project delay and overhigh cost caused by resource conflicts or insufficiency are reduced; and the risk management sub-module effectively reduces uncertain factors possibly encountered in a project execution process through identification, evaluation and formulation of countermeasures, so that the customer satisfaction is enhanced, and the market competitiveness and profitability of an enterprise are improved.

The invention discloses an engineering collaborative design management and control method and system based on digital twinning, and relates to the technical field of digital twinning, and the method comprises the steps: presenting a project design in a digital twinning model through a virtual reality environment based on a collaborative management matrix, carrying out the interactive design review and optimization, and generating an optimized design scheme; based on the optimized design scheme, the project team arranges task execution according to the design progress, and generates a task execution plan and resource scheduling data; monitoring actual execution conditions of the task execution plan and the resource scheduling data, and generating a quality control report by analyzing execution deviation and performing quality control; by automatically generating the task execution plan and the resource scheduling data, the design quality and the project management efficiency are improved, and the flexibility and the real-time performance in the project execution process are enhanced.

The invention provides a project execution process tracking and risk early warning method and system. The method comprises the following steps: collecting various data of a project in an execution process in real time; substituting various data of the project in the execution process into a pre-constructed autoregression integral moving average model to obtain an expected value related to the project; based on execution plan values in various types of data in the execution process of the project and the expected values related to the project, risk of project cost and progress is evaluated, and risk early warning information is generated; wherein the autoregressive integral moving average model is constructed based on time series data formed by various data of a historical project in an execution process in combination with a stationary analysis method. According to the method, the risk is predicted through the autoregression integral moving average model, various types of data in the project execution process are collected in real time, and the execution process of one project is comprehensively monitored, so that a project team is helped to deal with various potential risks more effectively.

A method for enabling collaboration between individuals to design, construct and maintain a building. The method comprises providing a network based computer system including at least one server and multiple clients. The multiple clients allow respective individuals to interact with the server. The server includes a machine-readable storage, which is encoded with software for execution by a CPU for allowing individuals at the respective clients to create, execute and manage projects associated with at least one of a design phase, construction phase and maintenance phase of the building. Each project comprises one or more events that are related to time. The method also comprises storing in the machine-readable storage events as they occur during execution of each project to create a building project database spanning at least the design phase and the construction phase and optionally the maintenance phase of the building.

The invention relates to an enterprise project informatization management method, device and system and a storage medium. The method comprises the steps of obtaining enterprise project internal data, enterprise project external data, initial fuzzy reasoning parameters and project execution historical data corresponding to a target enterprise; performing dynamic fuzzy reasoning on the enterprise project internal data and the enterprise project external data according to the initial fuzzy reasoning parameters to obtain dynamic fuzzy reasoning data; according to the dynamic fuzzy reasoning data and project execution historical data, identifying a relationship between each execution object and each task detail in the target enterprise to obtain project behavior analysis data; performing structured fusion on the dynamic fuzzy reasoning data and the project behavior analysis data to obtain enterprise project fusion data; and scheduling fixed resources and human resources of the target enterprise according to the enterprise project fusion data to obtain enterprise project management information. By adopting the method, the resource scheduling efficiency of the enterprise management project can be improved.

The invention discloses a dynamic optimization method for research and development project resource allocation, which comprises the following steps of: acquiring task state data and resource state data in a project execution process, constructing multi-source data and transmitting the multi-source data to a data processing center in real time; performing real-time monitoring on the multi-source data to obtain key indexes and resource pool states of research and development projects; based on a preset triggering rule, judging whether a triggering condition of resource redistribution optimization is met or not, and when the triggering condition is met, constructing a multi-target dynamic resource optimization model; solving the optimization model, generating a resource allocation scheme, and performing multi-dimensional evaluation to determine a final scheme; and executing the final optimization scheme, updating the project resource allocation state, and continuously collecting execution effect data for optimization adjustment, the research and development project resource real-time monitoring and dynamic optimization are realized, and the resource utilization efficiency and the execution quality of the research and development project are improved.

The invention discloses an innovative project decision prompting method based on AI model analysis, and relates to the technical field of innovative project monitoring, innovative project templates are constructed, a project core label is set for each template, a project execution mapping tree is designed according to project activity types, and each execution node of the mapping tree comprises project execution keywords and monitoring content; analyzing innovation project information through real-time semantic understanding, extracting project core labels and real-time activity progress information, and comparing the project core labels and the real-time activity progress information with templates to call corresponding templates; mapping the real-time progress information to an execution keyword, performing monitoring in combination with corresponding monitoring content, and generating warning content; according to the invention, real-time monitoring and accurate warning of the progress of the innovative project are realized, the intelligent level of project management is effectively improved, the project risk is reduced, and smooth promotion of the innovative project is ensured.

The invention relates to the technical field of science and technology intermediary services, in particular to a project management system which comprises a project information management module, a project progress tracking module, a resource docking matching module, a project execution and monitoring module, a communication module and a project achievement display module. And the project demand and the resource supply are accurately connected. The resource docking and matching module collects demand and supply information and shares the demand and supply information with the project information management module, so that task allocation is more scientific and reasonable. And the pre-estimation module cooperates with the project progress tracking module, pre-estimates resource investment time according to progress arrangement, and avoids resource idle waste. And the project execution and monitoring module performs task allocation according to the recommended resources, so that the resources are effectively utilized. The human resource recommendation unit recommends appropriate personnel according to task requirements and resource evaluation results, and the human resource utilization rate is improved.

The invention provides a full-life-cycle management method for an intelligent mixing station, belongs to the technical field of intelligent management of constructional engineering, and realizes full-process closed-loop management from production task issuing, production scheduling execution, progress monitoring to production information tracing through Internet of Things sensing, data collaboration and intelligent decision technologies. By breaking through a data barrier between a digital management platform and a mixing station control system, a'task-production-monitoring-feedback 'full-life-cycle management chain is constructed, dynamic optimal configuration of production resources is realized, and the engineering project execution efficiency and the resource utilization rate are improved.

To facilitate forming project execution plans.SOLUTION: A project support system 10 is configured to execute, by at least one processor, first processing s1 for acquiring requirements data 100, which records information related to requirement contents of a project, and second processing s2 for identifying departments most closely related to the requirement contents recorded in the requirements data 100.SELECTED DRAWING: Figure 1

The invention, which relates to the technical field of information management, discloses a construction engineering management system comprising a data integration module, an adaptive neural network module, a dynamic knowledge graph module, a probabilistic project simulation and optimization module, a multi-scale timeline analysis module, a transparent financial monitoring module, and a resource mobility optimization module. The self-adaptive neural network technology is adopted, the network structure and parameters can be automatically adjusted according to project characteristics, self-learning and optimization are achieved, uncertainty in project execution is simulated through a probability model, an optimization scheme of project execution is provided through an optimization algorithm, the project progress is analyzed on multiple time scales, and the project execution efficiency is improved. The system supports the adjustment of a project plan, optimizes the distribution and flow of resources according to the project progress and decision suggestions, reduces the resource waste, improves the resource utilization efficiency, each module has a clear function and responsibility, and forms a dynamic and adaptive project management cycle through the cooperative work of the modules.

The invention provides a project information processing method and device, equipment, a medium and a program product, and the method comprises the steps: responding to a field configuration operation for a node in a project, and displaying a field configuration interface; in response to an awakening operation for the work item of the work decomposition structure, displaying an interaction panel corresponding to the work item of the work decomposition structure in the field configuration interface; wherein the interaction panel comprises work items for displaying different levels of work decomposition structures; and according to different levels of work decomposition structure work items in the interaction panel, configuring a target field in a field configuration interface so as to establish a data transmission link between the target field and the work decomposition structure work items. According to the invention, information transmission between upstream and downstream nodes can be realized in a project execution process.