747 results about "Project management" patented technology

The invention relates to the technical field of management and control systems, in particular to a digital intelligence system applied to collaborative management and control of water-power engineering construction participating units, which comprises a project data management module covering water-power engineering construction full life cycle management, extracting multi-source information data from various subsystems, and constructing a project view and a project management information base; the project risk analysis module is used for constructing an intelligent risk analysis model for risk analysis and generating a dynamic evaluation result, a graded early warning notification and an auxiliary decision scheme; the project collaborative management module is used for processing graded early warning notification and auxiliary decision-making schemes by using a multi-layer perceptron model, and generating finalizing service achievements and management process records; and the project document management module is used for performing compliance automatic checking and processing on the electronic documents needing to be archived, and dynamically updating and optimizing the project management information base. Through the closed-loop management and control system, the cooperative management and control efficiency of water-power engineering construction participation units is improved.

The invention discloses a method for analyzing a matching degree between a demand and an output result based on text semantics. The method comprises the following steps: step 1, labeling a data set; step 2, technical document preprocessing; 3, training and predicting a single-parameter model; 4, integrating prediction results of the multi-parameter model; the method has the beneficial effects thatthe method is simple; deep learning and the NLP technology are applied to the field of project association degree calculation of enterprise project management for the first time. Calculating an association matching degree between the two projects according to project requirements and result description; the associated project positioning difficulty is effectively reduced; meanwhile, the demand side can be helped to quickly and efficiently locate high-quality projects adapting to the demand of the demand side; time and resource investment for achievement screening and matching are greatly reduced, the association matching degree between projects is calculated by means of text data of existing project achievement technical documents and project declaration guidelines, and then large enterprises are assisted in screening high-quality projects with the high matching degree in the project bidding and tendering link.

The invention belongs to the technical field of resource scheduling, and particularly discloses a resource scheduling method and system based on reinforcement learning, and the method comprises the steps: describing the dependency and conflict relation between tasks through constructing a task causal relation graph which can be dynamically updated; constructing a state space and an action space based on a current task state and a causal relationship, training an intelligent agent by adopting a reinforcement learning model in combination with a multi-target reward function, and generating a scheduling and resource allocation strategy; linear programming and heuristic joint resource allocation are carried out under strategy guidance, and task priorities and causal relationships are dynamically adjusted in combination with task states; by collecting execution data and analyzing strategy deviation, a model structure and parameters are further adjusted, and a complete closed-loop optimization process is formed. According to the method, task priority dynamic adjustment, resource allocation strategy self-adaptive updating and scheduling process closed-loop optimization are realized, and the method is suitable for complex project management scenes under multi-task and multi-resource constraints.

The invention discloses a construction project whole-process management system and method with a BIM3D-6D technology as a base, and relates to the technical field of construction project management, and the method comprises the steps: loading a 3D building information model through a BIM lightweight calculation server, extracting the spatial topological relation and IFC semantic attributes of geometric components, and carrying out the calculation of the 3D building information model through a BIM lightweight calculation server; spatial topology analysis and semantic attribute mapping are carried out on the spatial topology relation of the geometric components and the IFC semantic attributes, and a three-dimensional data topology network packet based on a graph structure is generated; performing multi-dimensional deduction operation on the three-dimensional data topology network packet based on the graph structure to obtain a deviation compensation strategy containing an optimal cost control path; and carrying out dimension expansion and data fusion on the 3D building information model to generate a 5D cost dimension data set. Discrete decisions are converted into a continuous field model through mathematical transformation, so that a resource flow path has spatial relevance and time continuity, and the beneficial effect of dynamically optimizing a construction process is achieved.

The invention relates to the technical field of project management, in particular to a large-model batch reasoning and data flow optimization system oriented to an MOE architecture. According to the method, a collaborative architecture of the request access module, the environment sensing module, the expert routing engine, the resource scheduling module and the dynamic optimization control module is set, the text length and the subject type are extracted by using the request access module, a basis is provided for accurate routing, and the GPU video memory, the I / O bandwidth and the request queue depth are acquired in real time through the environment sensing module, so that the real-time routing is realized. The system load is comprehensively monitored, meanwhile, an expert sub-network is activated through an expert routing engine according to request features, invalid calculation is avoided, weight loading and resource allocation are managed through a resource scheduling module, the I / O bottleneck is reduced, and finally an optimization strategy is intelligently triggered through a dynamic optimization control module based on routing conflict factors. The problems of large reasoning delay fluctuation and unbalanced resource utilization rate mentioned in the background technology are solved, and stable low-delay response and resource collaborative optimization in a high-concurrency scene is realized.

The invention discloses a large model cue word intelligent design and verification system supporting multi-person cooperation, which designs cue words in a manner of cue word project management and multi-person cooperation to realize specialized design of the cue words. The difficulty of cue word design is simplified by using AI aided design; the operation stability and accuracy of cue words in different models and different computing power are verified through single-point testing and batch testing, so that cue word verification and iteration form a closed loop, and the cue word quality is improved; after the cue word is published, directly outputting an interface with an access key for external calling, and storing the interface as a cue word case into a cue word knowledge base; compared with an existing system and technology, the cue word version management difficulty is effectively reduced, the workload of cue word designers is reduced, the cue word quality is improved, and the risk of cue word asset loss is reduced.

The invention relates to the technical field of performance evaluation, and provides an intelligent project performance evaluation and optimization platform which comprises a multi-source heterogeneous data fusion module, an association rule deep mining engine, a self-adaptive dynamic performance evaluation model, a closed-loop optimization decision module and an intelligent interaction system. According to the invention, an intelligent, dynamic and closed-loop project performance evaluation and optimization platform is constructed by fusing an advanced artificial intelligence technology and a project management theory, and the scientificity, refinement and intelligent level of project management is greatly improved.

The invention discloses a water conservancy project construction management informatization platform, and relates to the technical field of water conservancy project management, and the platform comprises an evaluation form generation module, a form filling verification module, an intelligent approval module, a classification filing module and a safety management module. According to the invention, a whole-user, full-service and full-life-cycle construction management standardization system is constructed; automatic filling and real-time verification are realized by means of a natural language processing technology and machine learning, and data entry experience and accuracy are improved; decision support is provided through big data analysis, a filling strategy and an approval path are recommended through a model, and process management is optimized; digitized upgrading of form full-life-cycle management is realized, and the method is suitable for a water conservancy project construction management scene with a complex approval process; the state evolution trend of hidden danger points or major hazard sources in a future period of time is simulated, and early warning and plan generation are carried out based on the state evolution trend.

The invention discloses an AI-based digital project performance evaluation data processing method and system, and relates to the technical field of artificial intelligence and digital project management, and the method comprises a multi-source data collection module which is used for obtaining data; the entity alignment module is used for establishing an association relationship among cross-system data entities; the dynamic index generation module is used for dynamically adjusting the evaluation index weight by utilizing a reinforcement learning framework; the efficiency prediction module is used for modeling a task dependency relationship according to the time sequence diagram convolutional network and outputting a delay risk probability; and the visual interface is used for displaying the data. According to the method, cross-system entity alignment, dynamic index weight adjustment, task delay risk prediction and root cause analysis are realized through AI technologies such as BERT semantic matching and a graph neural network, visual data display and interaction functions are provided by virtue of a visual interface, the problems of data dispersion, index static state, risk lag and the like in traditional project evaluation are solved, and the project evaluation efficiency is improved. And the decision support capability of project management is improved.

The invention relates to the technical field of data processing, in particular to a construction progress and resource collaborative prediction data processing method and related products, and the method comprises the steps: constructing a BIM knowledge graph; monitoring the real-time dynamic data in real time, and generating a multi-dimensional risk prediction vector if a risk event deviating from a construction plan is recognized; constructing a multi-objective optimization model, and solving to generate a collaborative optimization strategy; executing a collaborative optimization strategy, updating the construction progress plan and the resource allocation plan, and synchronously updating the BIM knowledge graph; according to the method, the BIM knowledge graph fused with the multi-source heterogeneous data is constructed, the information barrier between traditional BIM design data and field execution data is broken through, and the future time and cost deviation is predicted in a quantitative mode by performing linkage influence propagation simulation on risk events, so that the risk events are predicted more accurately. Project management is converted from a traditional'post remedy 'mode to a'pre-control' mode.

The present application relates to the technical field of project management, and discloses an integrated management system and method for a large-scale project. The system comprises: a budget subsystem, used for obtaining target project information, and carrying out multi-level classification processing and coding processing on the target project information to obtain budget codes; a contract management subsystem, used for decomposing the target project information, generating a plurality of project contracts and associating the plurality of project contracts with the budget codes; a construction management and control subsystem, used for splitting the project contracts to obtain unit projects, encoding the unit projects to obtain unit codes, and associating quantity data corresponding to the unit projects with a preset construction drawing list; and a joint control subsystem, used for carrying out joint control on the project cost, the project progress and the project quality on the basis of a measurement visa so as to carry out integrated management on a large-scale project. The present application realizes integrated management of large-scale project construction.

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.

A system and method for collaborative creation and management of intellectual property (IP) projects is disclosed. The system includes a server configured to dynamically assign roles and permissions to participants based on predefined criteria. A graphical user interface (GUI) facilitates real-time collaboration, editing, and version control, while a semantic analysis engine ensures compliance with intellectual property standards and assesses content novelty. Predictive analytics generate metrics, such as patentability scores and inventorship overlap, to guide project development. Contributions are electronically tracked and stored in a secure, non-transitory computer-readable medium alongside generated metrics. The system supports role-specific recommendations, automated notifications, and integration with external data sources for enhanced functionality. Participants can visualize contributions, resolve conflicts, and simulate commercialization outcomes, enabling efficient project management and innovation. This invention improves the collaborative development process, ensuring compliance, enhancing productivity, and maximizing the value of intellectual property assets.

The invention discloses a software development project progress prediction management method based on artificial intelligence, and relates to the technical field of project management, and the method comprises the steps: extracting a causal relation from entity relation graph data, and constructing a causal knowledge graph; a graph structure analysis method and a time sequence prediction method are combined, predicted completion time and delay probability are calculated for the causal knowledge graph and the associated time sequence data, and a progress risk assessment result is generated; performing causal chain identification on the progress risk assessment result and the causal knowledge graph by adopting a causal reasoning method to generate delay interpretation information; according to the delay interpretation information, a preset resource priority and a task weight, a rule driving and priority scheduling strategy is adopted to construct a compensation scheduling scheme; and implementing a compensation scheduling scheme, collecting implementation effect data and analyzing a scheduling effect through a closed-loop feedback and dynamic adjustment mechanism, and generating an optimized scheduling management scheme. The intelligent level and the practical value of project progress management are greatly improved.

The invention provides a BIM-combined construction process digital management method and system, and the method comprises the steps: firstly collecting a real-time three-dimensional model data set of a construction site, including geometric attributes and spatial topology association information of construction components, then analyzing the logic execution relation between different construction components, generating a progress scheduling rule set, and carrying out the construction process digital management. The actual construction progress data is dynamically matched with the set to obtain a construction process anomaly detection strategy and a resource allocation optimization strategy, then component parameter configuration of the real-time three-dimensional model data set is adjusted according to the anomaly detection strategy, updated three-dimensional model verification data is generated, and the updated three-dimensional model verification data is stored in a database. And finally, a construction progress adjustment instruction is generated according to the resource allocation optimization strategy and the updated three-dimensional model verification data, and is synchronized to the construction management terminal, so that digital and intelligent management of the construction process is realized, and the construction efficiency and the project management level are effectively improved.

The invention provides a building engineering project scheduling method based on multi-objective dynamic microphone optimization, and the method comprises the steps: firstly, building an optimization model with the minimization of the construction period, the minimization of the cost and the minimization of the resource fluctuation as targets, and enabling an objective function to cover the total construction period, the total cost and the resource fluctuation variance; secondly, designing an improved multi-target dynamic microphone optimization algorithm which ensures the feasibility and diversity of solutions through a dynamic elite retention mechanism, a mixed position updating rule, a three-layer constraint processing mechanism and a dual-threshold convergence monitoring system, so as to improve the robustness of the dynamic microphone optimization algorithm; and finally, solving the problem of the constructional engineering project by adopting a multi-target dynamic microphone optimization algorithm to obtain a construction project scheduling scheme. According to the method, on the premise of meeting resource limitation and task logic relations, the project construction period, the total cost and the stability of resource use are collaboratively optimized, automatic and intelligent optimization of the project scheduling process is realized, and the project management efficiency and scientificity are improved.

A multi-agent and human project management and collaboration tool can provide the ability to create and manage projects and software agents in a cohesive framework. The collaboration tool can provide a multi-agent, multi-player channel where agents and humans work together to achieve an outcome. The collaboration tool can initiate a new project, where the objective is defined, and a team is dynamically built to achieve this objective. The team roles are parsed, and an agent is created for each role. Each agent is equipped with a personalized skillset and a working memory, allowing them to effectively collaborate with humans and each other to progress autonomously through the project stages. The agents can complete tasks based on the project plan and the results are stored in the agent's working memory. The project status is updated, and a report can be generated after each stage, providing a record of the project's progress.

The invention discloses a foreground and background state information intelligent synchronization method in project management. The method comprises the following steps: S1, constructing a three-layer architecture of a foreground system, a state storage center and a background system; s2, initializing a state; s3, realizing state synchronization of the foreground system and the background system through at least one synchronization mode; s4, constructing a version control and conflict resolution mechanism, when the state of each project is updated, the foreground system and the background system carry version numbers, checking the consistency between the client version number of the foreground system and the server version number of the background system when the update is submitted, if the client version number of the foreground system and the server version number of the background system are consistent, executing state updating and progressively increasing the version number, and if the version number of each project is not consistent, executing state updating and progressively increasing the version number; if yes, judging that the data conflict exists, automatically executing a preset conflict solving strategy, and broadcasting a resolution result to a foreground system and a background system. The method has the advantages that the item switching state is not lost, background state change and foreground real-time response are achieved, and conflicts are automatically eliminated without manual intervention.

The invention provides an intelligent project management method and system for project supervision, and relates to the technical field of project supervision, and the method comprises the steps: taking a structural member and a construction technology in a construction drawing as a basis, extracting a risk supervision unit with a space anchor point and a supervision priority through a semantic matching and structural modeling mode, and carrying out the construction of a project. The risk units serve as the minimum execution entity of the supervision task, the future disturbance trend of each risk unit is predicted based on the time sequence modeling technology in combination with field IoT data and the construction progress, and the dynamic risk score of the risk unit is calculated according to the future disturbance trend; by using the scoring system, through a matching algorithm and a scheduling optimization model, dynamically generating an optimal scheduling suggestion of the supervisor, and continuously recording supervision behaviors of the supervisor on site; all supervision behaviors are subjected to semantic alignment with drawing specifications in a structured filing mode, the behavior quality is judged through a consistency scoring mechanism, and acceptance suggestions or rectification actions are triggered on the basis; and the consistency of the supervised object and the drawing target is ensured.

The invention discloses an intelligent project implementation management system and method based on multi-source perception fusion, and aims to solve the problems of information isolated island, response lag, experience dependence, extensive management and control and the like in an engineering project. According to the system, multi-source data acquisition is carried out through an Internet of Things sensor, a video monitor, a mobile terminal, a BIM / GIS, a project management platform and the like, and after space-time alignment and standardization processing are carried out, a unified situation awareness view is constructed by adopting a hierarchical fusion strategy; performing real-time intelligent evaluation and prediction on progress, quality, safety, cost and resources based on the fused data; a rectification, scheduling or early warning instruction is automatically generated, and a sensing-analysis-decision-execution closed loop is realized by pushing and linking a field execution system through multiple channels; according to the method, the safety prevention and control, quality control and progress performance capabilities are remarkably improved, the accident rate and cost are reduced, and project management is promoted to be transformed and upgraded to a refined, active and self-evolution direction.

The invention discloses a project management method and device, electronic equipment, a storage medium and a program product, and relates to the technical field of software development control, and the method comprises the steps: managing the construction path, output path and other information of a nested warehouse project through a unified configuration file, and achieving the centralized definition of a multi-project construction process; the problem of packaging dispersion caused by separate management of the sub-modules is avoided; the unified construction environment is initialized based on project information of centralized configuration, it is ensured that the dependency relationship of all modules and the construction process are coordinated and consistent, and the stability and reliability of the construction process are enhanced; command generation logic is constructed in a standardized mode, configuration complexity and later maintenance cost are reduced, and unified management and control of the process are achieved; through a centralized management mode driven by configuration, the defect of processing multi-warehouse construction deployment depending on manual scripts is eliminated, repeated labor is reduced, and development efficiency and project agility are improved.

The invention relates to an electric power project demand similarity analysis method based on a rearrangement model and retrieval enhancement generation, and belongs to the technical field of computer science, artificial intelligence and natural language processing. The method comprises the following steps: constructing a multi-modal knowledge base; after user query is received, self-adaptive query expansion is carried out through a large language model, preliminary recall is carried out by adopting a mixed search strategy, secondary accurate scoring and reordering are carried out on candidate lists by utilizing a rearrangement model of a cross encoder framework, and a final result is generated in combination with an interpretability analysis technology. And finally, driving the large language model to generate a multi-dimensional intelligent analysis report through chained thinking prompt. According to the method, the problem of analysis deviation caused by low retrieval quality in a traditional RAG method is solved, the transparency of the system is enhanced through interpretability analysis, and the finally generated multi-dimensional analysis report can provide unprecedented decision support for project management.

The invention relates to the technical field of project management intelligent decision making, in particular to a project management intelligent decision making system integrating multi-target resource scheduling optimization. The system comprises an equipment state sensing module, an environment monitoring module, a data acquisition module, a conflict evaluation module and a dynamic decision module. The equipment state sensing module is used for collecting operation parameters of key construction equipment in real time, wherein the operation parameters comprise equipment real-time position coordinates, actual speed, fault early warning coefficients, actual working time and actual completion time. The data acquisition module is used for acquiring supply chain data and construction plan data. The equipment state sensing module, the data acquisition module and the environment monitoring module are arranged for cooperative use, so that the system can automatically sense environment changes such as wind speed and wind direction, the equipment offset risk is calculated through the conflict evaluation module in real time, and meanwhile, the resource scheduling instruction is generated, so that the error correction response time is greatly shortened, and the error correction efficiency is improved. And meanwhile, the delay time of the construction period is reduced.

The invention discloses a water conservancy project management method and system based on multi-source inspection data fusion and correlation analysis, and relates to the technical field of data processing. According to the method, hierarchical coding is performed on the inspection data in a unified acquisition period, and a three-layer envelope structure is constructed, so that time-space integrated organization of multi-source inspection information is realized, cross-source data is enabled to obtain structural consistency expression, and the accuracy and traceability of data fusion are improved; according to the method, a joint positioning point is established in a time envelope layer and a collaborative labeling identifier is distributed in a space envelope layer, so that collaborative labeling entries with synchronous semantics are formed by data of different sources, and the alignment capability and the contrastive analysis efficiency of inspection information are remarkably improved; by means of construction of a step-by-step linkage association link, continuous evolution of a water conservancy structure state can be presented on a time sequence, meanwhile, spatial-temporal characteristics can be synchronously captured in combination with generation of dynamic association paragraphs, and the recognition sensitivity of abnormal changes is enhanced.

The invention discloses an enterprise project database intelligent management method and system, and relates to the technical field of data management and resource optimization. The method comprises the following steps: verifying the integrity of business unit project data in real time through an intelligent cleaning engine, and structurally storing the business unit project data to a central project database; integrating the progress, the cost, the risk field, the commercial value and the strategic weight to dynamically calculate a comprehensive value index; based on the value index and the real-time resource inventory, a resource allocation scheme is generated through a hierarchical adaptation strategy, and a priority list is output; tracking progress deviation during execution, and triggering data isolation and index optimization when risk offset exceeds a threshold value; risk root causes are analyzed, value weights are dynamically adjusted, a rule base is managed in a back-feeding mode, and system self-optimization is achieved. According to the method, the problems of resource allocation rigidness, risk response lag and lack of dynamic value guidance in traditional project management are solved, the resource utilization rate is improved, and the project delay risk is reduced.

The invention relates to the technical field of constructional engineering management, and discloses a constructional engineering construction progress early warning method and system based on machine learning, and the method comprises the steps: collecting multi-dimensional original data from a construction site sensor, a BIM model, IoT equipment and a historical database; features related to the construction progress are extracted from the multi-dimensional original data, the extracted features are combined and transformed, and composite features are obtained; inputting the composite features into a progress prediction model, predicting the construction progress in a period of time in the future through the progress prediction model, and outputting a prediction result; the method comprises the following steps: determining an initial early warning threshold value by analyzing historical construction data, and dynamically adjusting the early warning threshold value according to real-time monitoring data and a prediction result in a construction process; when the construction progress deviates from the prediction progress and exceeds the early warning threshold value after dynamic adjustment, early warning is triggered; according to the method, the adaptability to a complex construction environment and the prediction accuracy are improved.

The invention relates to the technical field of engineering project management, and discloses an engineering project supply chain collaborative management system, which comprises a unified data interface module used for acquiring multi-source business data from heterogeneous information systems of an engineering project general package party, a sub-package party, a material supplier and a logistics service provider, processing the multi-source business data into a standardized business data model; and a business process management module. By adopting the technical scheme that a unified data interface module and a workflow engine cooperatively work, the technical effects of connecting information systems of all participants of a supply chain and realizing automatic synchronization of purchasing, inventory and construction progress data and linkage of a business process are achieved; compared with the technical scheme that each party adopts an incompatible information system and depends on manual information transmission in the prior art, the defect that the accuracy of a project plan is damaged due to difficulty in collaborative operation caused by data obstruction is overcome.

The invention discloses a digital project management method and system based on artificial intelligence, and relates to the technical field of project management, and the method comprises the steps: constructing a project digital portrait and multi-dimensional feature analysis framework, determining an analysis domain boundary of intelligent auditing, and automatically generating an intelligent analysis grid adaptive to multi-source heterogeneous data; and performing grid division on project progress data according to an analysis domain boundary, performing adaptive partition on a project grid through an unsupervised clustering algorithm, dynamically determining a critical threshold value of risk early warning based on a project digital portrait and intelligent analysis grid and comprehensive risk stress analysis, and outputting a risk early warning decision management conclusion containing the critical threshold value. According to the management system, an intelligent analysis grid adaptive to multi-source heterogeneous data is generated by constructing a project digital portrait and a multi-dimensional feature analysis framework, and a risk early warning critical threshold value is dynamically determined, so that real-time perception, accurate analysis and intelligent decision support of the full life cycle state of a project are realized.

Embodiments described herein relate to systems and methods for automatically generating content, generating API requests and / or request bodies, structuring user-generated content, and / or generating structured content in collaboration platforms, such as documentation systems, issue tracking systems, project management platforms, and other platforms. The systems and methods described use a network architecture that includes a search and chat generative interfaces, which may be used to produce generative answers, identify relevant content, and take actions within a respective content collaboration platform.

The invention relates to an application that utilizes artificial intelligence to enhance project management in construction and repair industries. The system includes a user computing device, an application server, and a database server. The application server processes project data, including blueprints, to generate materials lists, integrates with online marketplaces to facilitate purchasing, and employs machine learning for product recommendations. The system also uses predictive analytics to forecast project deliveries and prevent backorders, while optimizing resource allocation through efficient supplier and material selection. The software application features an AI-powered chat, job planner, marketplace, and cart, providing a comprehensive platform for real-time collaboration among contractors, suppliers, and manufacturers. This innovation streamlines project workflows, reduces errors, and improves overall efficiency in managing construction and repair projects.