1250 results about "Project management" patented technology

The invention relates to the technical field of engineering progress management, in particular to an engineering construction digital project management method and system, and the method comprises the steps: database building, real-time data collection, and model building: generating a visual construction progress model; progress deviation judgment: calculating progress deviation and performing judgment; deviation analysis: calculating a resource gap of an affected process, and generating a resource allocation priority list; resource adjustment: pushing an adjustment instruction to the construction terminal according to the priority list; simulation: simulating the adjusted construction progress, and if the deviation is not eliminated, executing a redistribution step; redistribution: executing the deviation analysis step again; and optimization: optimizing subsequent project progress plan generation logic. The system comprises a database building module, a real-time data acquisition module, a model building module, a progress deviation judgment module, a deviation analysis module, a simulation module, a redistribution module and an optimization module. The method and the device have the effect of facilitating fine management of the engineering project.

The invention relates to the technical field of project management, in particular to an intelligent management method and system for a civil engineering project, and the method comprises the following steps: obtaining personnel distribution, equipment state and material inventory data, extracting a key task node and an execution state, recognizing a progress lagging task, screening a key path node, analyzing a time difference, and marking a progress trend. And identifying an equipment influence section, judging resource allocation imbalance, and generating a progress monitoring index. According to the invention, through multi-source data acquisition of personnel distribution, equipment state and material inventory, difference identification between a task state and a plan node is enhanced, progress lag early warning efficiency is improved, progress fluctuation dynamic classification and trend identification are realized, construction rhythm optimization is assisted, and through coincidence analysis of equipment operation and a task fluctuation area, the progress lag early warning efficiency is improved. The construction efficiency bottleneck is identified, the scheduling accuracy is improved, fine progress monitoring is realized through investment and period difference comparison, and the progress control capability and the collaboration of on-site resource allocation are comprehensively enhanced.

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 relates to the field of information management, and discloses a constructional engineering information management system, which comprises a data acquisition module, an intelligent analysis module, a risk prediction module, a resource optimization module and a feedback learning module, the data acquisition module is used for acquiring multi-source data related to constructional engineering; the intelligent analysis module carries out fusion, preprocessing and feature extraction on the collected data; the risk prediction module predicts possible risks in the future by using a statistical analysis model; the resource optimization module dynamically adjusts and optimizes manpower, equipment, materials and process arrangement of the construction site according to the risk prediction result; and the feedback learning module is used for collecting a system execution result, risk prediction accuracy and user feedback, and recording an optimized execution result. The method has the advantage of realizing efficient engineering management and decision support.

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 discloses an intelligent construction method based on data driving, and relates to the field of intelligent construction, and the method comprises the steps: collecting multi-source heterogeneous data of an intelligent construction project; performing feature selection on the acquired multi-source heterogeneous data by adopting a recursive feature elimination (RFE) algorithm to obtain a feature subset reflecting project progress, quality and safety; according to the feature subset, a multi-target model used for predicting project progress, quality and safety is constructed through a support vector machine (SVM) algorithm; a non-dominated sorting genetic algorithm NSGA-II is adopted to solve the multi-target model, a simulated annealing strategy is introduced in the iterative search process of the NSGA-II to jump out of a local optimal solution, and an optimized Pareto optimal solution set is output; and selecting an optimal parameter combination according to the Pareto optimal solution set, and adjusting the BIM model of the current intelligent construction project by using the optimal parameter combination. In view of low multi-objective optimization efficiency in intelligent construction project management in the prior art, the optimal model parameters considering different management objectives are obtained, and the efficiency is improved.

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.

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 generative interface panel having multiple automated assistant services. Each assistant service may access a prompt generation service and a set of one or more purpose-configured large language model instances (LLMs) and / or other trained classifiers or natural language processors used to provide generative responses for content collaboration platforms.

The invention provides a project management method, system and device and a medium, and belongs to the field of project management. The method comprises the following steps: collecting project related data, and sorting and cleaning the project related data to obtain a structured data set; adopting an entity identification and relation extraction algorithm to carry out entity labeling and relation extraction processing on the structured data set so as to construct a knowledge graph related to the project; the method comprises the following steps: performing task decomposition by adopting a graph traversal algorithm on the basis of a knowledge graph, generating a task list and a priority sequence thereof, and monitoring task progress and resource utilization rate in real time on the basis of a dynamic optimization algorithm so as to dynamically adjust task priority and a resource configuration strategy. The task module is automatically decomposed based on the knowledge graph, the task decomposition efficiency and accuracy are improved, intelligent resource allocation and task priority adjustment are achieved in combination with dynamic planning and an optimization algorithm, the team cooperation efficiency is improved, and the flexibility and adaptability of a project are improved.

The invention relates to the technical field of project management, in particular to a BIM-based building project resource scheduling optimization method, which comprises the following steps: based on the current progress state of a construction task, collecting the consumption of constructors, mechanical equipment and materials, comparing the task plan progress with the real-time progress, screening out construction links with the backward task progress, and establishing a construction project resource scheduling optimization model; and judging a resource type, and establishing a task progress offset. According to the method, the construction progress is accurately monitored, real-time evaluation of resource consumption is achieved, waste and scheduling lag are avoided, the construction path is optimized by means of the BIM model, the key path monitoring precision is improved, progress management and control effectiveness is ensured, key path progress deviation is analyzed, the resource shortage risk is recognized, stable supply of construction resources is guaranteed, and on the basis of the influence of resource shortage, the construction efficiency is improved. The resource distribution sequence is optimized, the resource utilization efficiency is improved, the supply chain delivery cycle is matched, the resource scheduling is optimized, the influence of resource supply and demand imbalance on the construction progress is reduced, and the continuous and stable construction progress is ensured.

The invention relates to the technical field of project management, in particular to a building engineering project construction quality management method and system, and the method comprises the following steps: obtaining a drawing node sequence index and comparing a process stage number, screening compliant nodes, judging the reasonability of a task configuration time sequence, analyzing the deviation of an included angle between a crack angle and a load direction, and recognizing structural abnormality. And aggregating the partition abnormal nodes to form a construction project quality risk distribution section mapping result. According to the method, the structure drawing node sequence is compared with the construction process, it is guaranteed that input data logic is unified, the task configuration reasonability is improved through input time and stage sequence cross check, a stress deviation judgment mechanism is established in the crack direction through vector included angle and load comparison, and structural logic verification of inspection data is achieved; abnormal nodes are identified according to double standards of time compliance and stress deviation, a spatial density model is constructed by combining partition aggregation with an area ratio, building quality risk distribution is accurately presented, and the problem focusing and processing priority judgment capability is enhanced.

The invention relates to the technical field of engineering project management, and discloses an engineering project progress intelligent monitoring method and system. The method comprises the following steps: acquiring progress parameters including a task completion state, resource consumption and the like in real time through a multi-source data acquisition terminal; inputting the parameters into a preset anomaly detection model to identify and mark abnormal data segments, wherein the model dynamically adjusts a threshold value according to historical data characteristics; inputting the marked parameters into a collaborative prediction model to generate a progress trend prediction result, and carrying out multi-dimensional fitting on the model according to a task dependency relationship and a resource allocation weight; and finally, classifying and integrating the prediction result and the current progress parameter by using a priority scheduling algorithm to form a dynamic monitoring data set for storage. According to the invention, intelligent monitoring of the progress of the engineering project is realized, the monitoring accuracy and timeliness are improved, project delay and cost increase can be effectively prevented, and the project management efficiency is improved.

A prefabricated building component stability monitoring and early warning method and system, relating to the technical field of engineering project management. The method comprises: on the basis of a target building engineering drawing, constructing a construction node sequence; generating a plurality of engineering construction simulation models; acquiring a sample data set of a plurality of construction nodes, performing stability-associated factor analysis, and constructing a node factor mapping sequence; by using the node factor mapping sequence as monitoring data, performing construction monitoring, and determining construction monitoring data of a first construction node; on the basis of the construction monitoring data, performing mapping and acquiring a first engineering construction simulation model, performing error analysis by means of a twin comparison channel, and determining a first construction error; and on the basis of the first construction error, generating a construction early warning signal, and, on the basis of the construction early warning signal, acquiring a first construction compensation parameter and performing subsequent construction compensation for target building engineering, thereby achieving the technical effects of improving the safety and reliability of a prefabricated building structure and reducing potential risks and losses.

The present invention provides a multi-project scheduling optimization algorithm and system based on resource constraints. By loading test tasks, personnel information and equipment status, a task dependency graph is constructed to determine the execution order. Through the priority calculation module, each task is assigned a priority according to the deadline, resource requirements and task urgency, ensuring that high-priority tasks are executed in a timely manner. The scheduling execution module uses the shortest job first (SJF) or backtracking algorithm to optimize task scheduling. In addition, the real-time monitoring module monitors the task progress and resource status, and the conflict detection and processing module can adjust the personnel and task allocation in real time to cope with resource contention. Finally, the evaluation and optimization module generates an evaluation report after the project is completed, records the resource utilization efficiency, and provides improvement suggestions for subsequent projects. The present invention effectively improves the efficiency of multi-project management in a resource-constrained environment, and is suitable for scientific research, engineering and other multi-task collaborative fields.

The invention belongs to the technical field of project management, and discloses a project management big data dynamic optimization method, which comprises the following steps: acquiring project optimization information; constructing a project knowledge graph, and performing graph traversal on the project knowledge graph based on the real-time task set of the project needing to be managed to obtain a corresponding dynamic sub-graph; image reasoning is carried out based on the obtained dynamic subgraph, corresponding project expected information is obtained, whether project risks exist in the project needing to be managed or not is judged based on the project expected information, and if the risks exist, corresponding risk early warning information is generated; and constructing a standby coping strategy set based on the risk early warning information, performing strategy selection optimization based on the dependency relationship among the data nodes in the dynamic subgraph to obtain a corresponding optimal coping strategy, performing real-time monitoring on the execution process of the corresponding optimal coping strategy, and performing information feedback based on the monitoring result. According to the invention, the overall level and efficiency of project management are significantly improved.

The invention belongs to the technical field of text data processing, and particularly discloses an LLM-based contract element extraction and auditing method and device, and the method comprises the steps: analyzing a target contract to obtain text block data, carrying out the vectorization processing of the text block data to obtain a first multi-dimensional vector, and constructing a text vector database; extracting feature information in the to-be-processed text and taking the feature information as a contract index, generating a label of the contract index according to a category to which the feature information belongs, and vectorizing the feature information and the corresponding label to obtain a second multi-dimensional vector; searching first multi-dimensional vectors similar to the second multi-dimensional vectors in a text vector database, and sorting all the second multi-dimensional vectors to generate a vector sequence; generating a to-be-checked contract according to the vector sequence and the text block data, and labeling the to-be-checked contract through the difference between the first multi-dimensional vector and the second multi-dimensional vector; the method has the advantages that the indexes can be automatically extracted, the verification result containing explanation can be given, and the working efficiency of project management personnel can be remarkably improved.

The invention provides a prefabricated pipe pile construction total factor intelligent management method and system based on the digital twinborn technology, and relates to the technical field of construction management, a three-dimensional model is established through the BIM technology, pipe pile attributes are bound, construction data are collected in real time through the Internet of Things, and a dynamic digital twinborn body is formed. Through integration of an API interface and a project management platform, an AI algorithm is used for analyzing data, resource allocation and construction plans are dynamically adjusted, instructions are optimized and pushed to the site, construction efficiency and installation precision are improved, and the problems that traditional management is low in efficiency and large in error are solved.

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 provides a project management software document uploading method based on OCR and a large language model, and relates to the technical field of large language models, and the method comprises the steps: receiving a project document picture, and carrying out OCR recognition through a multi-scale feature pyramid and an attention-enhanced convolutional neural network; inputting the text information into a pre-trained large language model for classification and key field extraction; determining a data partitioning strategy according to the item type to create a storage space; establishing a multi-dimensional index structure to store project information and analyzing a content logic relationship; and generating and displaying a project information relation graph. According to the invention, intelligent identification, classification and correlation analysis of the project documents are realized, and the project management efficiency and the data utilization value are improved.

The invention discloses an engineering construction quality safety risk management system, and belongs to the technical field of safety risks. Comprising a project management module, a quality safety risk management and control module, a compliance review and data analysis module, an integrated project management module, a risk identification and evaluation module, a risk prevention and control strategy module, a dynamic monitoring and early warning module, an accident handling and tracing module, a compliance review auditing module and a data analysis report module. According to the invention, basic information and design parameters of construction projects are collected through the project management module, a BIM model is established, construction simulation, conflict detection and resource optimization are carried out, an actual construction plan and schedule are formulated, multivariate data in the construction process are collected in real time, early recognition, evaluation and positioning of construction safety quality risks are realized by using the model, and the construction safety quality risk is evaluated and positioned. A risk prevention and control strategy is formulated, key parameters are monitored in real time, early warning is given out immediately when data exceed a threshold value, a risk model and prevention and control measures are improved, and efficiency and safety are improved.

The invention provides an intelligent project management method and system based on enterprise digital information. According to the method, firstly, real-time process data and dynamic image data in an enterprise project are collected, and the dynamic image data cover operation records and a project initial framework; then, extracting a personnel action track and an equipment state from the image data, forming an operation feature set comprising operation coherence parameters and abnormal frequency, analyzing a sequential logic relationship of process data, and generating a standard project task book containing a task decomposition structure; then, the information is matched and converted into multi-dimensional management parameters containing dynamic task priority weights, a dynamic process topological structure isomorphic to the standard task book is constructed based on the multi-dimensional management parameters, and a real-time feedback path is embedded in the dynamic process topological structure to trigger version iteration of the standard project task book. According to the technical scheme provided by the invention, the efficiency and flexibility of intelligent project management can be improved.

The invention relates to the technical field of enterprise project management, and discloses an enterprise project management method and system based on multi-source heterogeneous data integration, and the method comprises the steps: receiving heterogeneous data from a plurality of data sources; classifying the heterogeneous data into different-speed data streams of a high-speed stream, a medium-speed stream and a low-speed stream according to the updating frequency; allocating a logic timestamp for the different-speed data stream; the different-speed data flow is processed based on the logic timestamp, and the logic consistency of data processing is guaranteed; converting, aggregating and analyzing the processed data according to a preset data stream processing logic; the analysis result is applied to enterprise project management decision support; real-time performance, consistency and integrity of data in enterprise project management are achieved, efficiency and decision quality of enterprise project management are improved, and the problems of data islands, data inconsistency and data processing lag in traditional enterprise project management are solved.

The invention relates to the technical field of engineering cost dynamic measurement and calculation, in particular to an intelligent engineering cost dynamic measurement and calculation and cost control method and system. Comprehensive influence factors of nodes can be extracted from a complex construction task incidence relation through a graph convolutional network; comprising resource intensity, progress sequence and potential resource conflict problems, so that accurate identification of key construction paths is improved, the real-time feedback capability of project progress and cost is enhanced, dependence of a traditional budget model on static factors is effectively avoided, project decision is optimized according to real-time changes, and the construction efficiency is improved. The efficient distribution of budget and resources is ensured, through the application of the non-dominated sorting genetic algorithm, and according to the residual budget, the construction period and the resource value, comprehensive evaluation and node screening optimization are carried out, so that project management can flexibly adjust the budget and the construction period based on the actual situation, the situation of unreasonable fund scheduling or resource waste is avoided, and the project management efficiency is improved. And the accuracy and flexibility of engineering project management are improved.

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 an enterprise project intelligent visual management method based on big data, and belongs to the field of data visualization, and the method comprises the steps: collecting original data related to an enterprise project; preprocessing the original data to obtain a structured project data set; analyzing the project data set to obtain a project management mode and a project management rule, and constructing a project management knowledge graph based on the project management mode and the project management rule; a visual management platform is built, an interactive visual interface is generated in combination with the project management knowledge graph, and multi-dimensional visual display of the whole life cycle of the project is achieved. The technical problems that in the prior art, enterprise project management data is dispersed, effective integration and analysis are lacked, and project progress and risks are difficult to master comprehensively are solved, the project management knowledge graph is constructed based on big data analysis, full-life-cycle multi-dimensional visual management of projects is achieved, and the project management efficiency is improved. And the project management efficiency and the decision level are improved.

A system for managing digital transformation projects, consisting of: • a processing unit configured to execute a variety of instructions in real time during the lifecycle of the digital transformation project to perform risk assessment, quality control, and dynamic compromise optimization; • a storage unit coupled to the processing unit, wherein the storage unit stores project data, risk categories, predefined quality metrics and resilience indicators; • a user interface module configured to display project performance metrics, including risk levels, quality status and resilience indicators, and to allow user interactions for real-time adjustment of project parameters; • A communication module configured to synchronize project data with external systems, databases and cloud-based platforms, ensuring seamless data exchange and real-time reporting between multiple project management tools and stakeholders.

The invention belongs to the technical field of building project management, and particularly relates to a building curtain wall assembly management technology, in particular to a building engineering project management intelligent system and method. A three-dimensional matrix including component identification, material consumption, a planned entering time window and a material sensitivity label is constructed based on a component entering plan; meanwhile, a construction site space model is established, the occupation state of a three-dimensional matrix simulation material storage yard is loaded in the model according to a component entering plan, and component entering is dynamically optimized by comprehensively considering storage yard space overlapping and meteorological adaptability factors in combination with meteorological prediction data in an assembly time window; prejudgment and adjustment of the assembly plan before implementation are realized, and the change frequency in the actual execution process is effectively reduced, so that the waste of manpower and material resources is remarkably reduced, and the stability and efficiency of a construction organization are improved.

The invention discloses a method, a system, equipment and a medium for analyzing project progress based on a BIM model and an AI video, and relates to the technical field of constructional engineering management, and the method comprises the steps of collecting regional image data, and executing semantic segmentation and environment modeling. And constructing a multi-scale spatial feature network and a dynamic skeleton modeling engine, inputting the three-dimensional environment diagram, the structure recognizable region diagram and the obstacle probability distribution diagram into the multi-scale spatial feature network and the dynamic skeleton modeling engine, and outputting execution structure recognition and defect anomaly labeling. And triggering an engineering response mechanism based on the risk event scoring function and remotely and dynamically adjusting the construction path. According to the method, through a mode of combining semantic segmentation and three-dimensional environment modeling, high-precision structure identification of the construction site image is realized, and the problems of unclear structure identification and fuzzy component boundary in traditional video monitoring are effectively solved.

The invention discloses an EPC project resource dynamic scheduling method based on multi-objective optimization, and the method comprises the steps: extracting project starting time and activity attributes from an EPC project, constructing a project activity list and a project resource list, constructing a multi-objective function, a decision variable and a constraint condition, and carrying out the dynamic scheduling of the EPC project resource. And processing the project activity list, the project resource list and the project starting time by using a multi-objective optimization algorithm containing crossover and mutation operation to obtain an optimal resource scheduling scheme containing the project construction period, the cost and the resource utilization rate, and after the scheme is issued and executed, obtaining the progress, the cost and the resource use condition in real time, thereby realizing the resource scheduling. A progress deviation rate, a cost performance index and a resource load rate are calculated and normalized, a comprehensive evaluation value is obtained through a linear weighting model, and whether a multi-objective optimization algorithm is optimized or not is judged according to the comprehensive evaluation value, namely, the weight of each objective function is adjusted according to the highest index after normalization, and a scheme is regenerated. According to the invention, resource dynamic optimization scheduling is realized, and project management efficiency is improved.

The invention, which relates to the technical field of mineral product screening, discloses an intelligent construction management platform for city updating, comprising the following steps: establishing a unified data standard and a data interface protocol to ensure that data of different systems, departments and enterprises in the platform can be seamlessly jointed; according to the invention, through unifying the data standard and the interface protocol, data sharing of different systems is realized, and project management efficiency and decision accuracy are improved. The real-time data acquisition and intelligent analysis technology enhances the safety monitoring and intelligent early warning functions, and ensures that potential safety hazards in the construction process are recognized and processed in time. Meanwhile, the flexibility and the emergency response capability of the project are improved by a dynamic adjustment and intelligent early warning mechanism, resources and construction plans can be automatically adjusted in the progress of the project, emergency problems can be dealt with, progress delay and resource waste are reduced, and smooth progress of the project is guaranteed.