24 results about "Project cost management" patented technology

The invention provides a municipal drainage project cost risk prediction and control method based on big data and artificial intelligence, and relates to the technical field of project cost management. Comprising the steps of obtaining multi-source heterogeneous data such as design and engineering quantity, construction progress, change visa, geology, hydrology and meteorology, operation monitoring, history and market, macropolicy and Internet of Things sensors, and performing fusion preprocessing; cross-source space-time alignment and entity association are realized based on unified coding and timestamps, and a target feature set is determined in combination with business semantics and a space-time relationship; constructing a graph structure for describing the space-time dependence of the project elements; setting risk measurement based on a cost control reference, and training the model in real time; inputting the graph structure into a model to generate a risk prediction result; and multi-objective optimization is carried out according to prediction, and early warning measures are generated and risk measurement is adjusted in real time under the constraint of contract policies, resource capabilities, time window processes and drainage safety by integrating the cost risk, progress deviation and disposal cost, so that closed-loop control from data to decision is realized.

The invention discloses a big data analysis and automatic evaluation system in project cost consultation, and relates to the technical field of big data analysis and evaluation. By constructing a unified data acquisition framework and a dynamic updating mechanism, efficient integration and real-time interaction of multi-party heterogeneous data are realized, data transparency and reliability are remarkably improved, a solid data basis is provided for project cost management, the system quickly and accurately optimizes various variables by utilizing comprehensive analysis and multivariable optimization technologies, and the system has a good application prospect. The system adapts to the dynamic environment, enhances the anti-risk capability of the project, ensures that the project cost management meets the real-time requirement and realizes the globally optimal solution, and in addition, through resource allocation strategy generation, view updating and decision recording and a feedback loop mechanism, the system realizes the generation and continuous improvement of a resource allocation strategy oriented to global benefit balance. The resource allocation efficiency and the long-term competitiveness of the project are improved, and powerful support is provided for sustainable development of urban construction.

The invention relates to the technical field of power grid project cost management and business intelligence, and discloses a project cost multi-stage intelligent analysis and examination method, system, equipment and medium, and the method comprises the steps: building a power grid project cost data warehouse, and achieving the integration and standardization of multi-source cost data; establishing an OLAP multi-dimensional analysis model, and supporting general cost comparison and key index analysis in a budget calculation stage, feasibility research estimation, preliminary design budget calculation, completion settlement three-calculation comparison, first supply material check and review list consistency check in a settlement stage; designing an intelligent decision engine based on data mining, and generating review opinions through association rules, a classification algorithm and an anomaly detection technology; and a BI visual instrument panel is developed, and multi-dimensional display, real-time monitoring and interactive analysis of the power grid cost data are realized. Through systematic application of the BI technology, deep mining, intelligent decision and visual display of engineering cost analysis are realized, and the efficiency and precision of cost review are remarkably improved.

The invention relates to the technical field of engineering cost management, in particular to a digital building engineering project cost management system. The system comprises a data acquisition layer, an intelligent analysis layer and a decision output layer, the data acquisition layer is used for sequentially and continuously acquiring physical quantity data, BIM component-level engineering quantity data, market price data and carbon emission activity data of a construction site; the intelligent analysis layer integrates a learning cost prediction model, a BIM-cost mapping engine, a cost deviation traceability knowledge graph and a reinforcement learning simulation module; the decision output layer deploys a dynamic budget adjustment mechanism of block chain evidence storage and executes a carbon cost measurement model; according to the dynamic budget adjustment mechanism of the block chain evidence storage, each budget adjustment is submitted to a permissible block chain network in a smart contract form, and a budget change voucher which cannot be tampered is generated after consensus of multiple nodes; and executing the carbon cost measurement model for calculating the marginal carbon cost in real time and dynamically injecting the carbon quota transaction price into the cost prediction model.

The application discloses an engineering project cost whole-process collaborative management method and system, relates to the technical field of engineering project cost management, and comprises a cost matter main line construction module, which is used for receiving project estimation, design budget estimate, bidding control price, contract price, process measurement, change visa, claim and item data of final account, performing unified matter code mapping and cross-stage integration processing, and generating cost matter unit data. In the application, the project estimation, the design budget estimate, the bidding control price, the contract price, the process measurement, the change visa, the claim and the item data of the final account are subjected to the unified matter code mapping and the cross-stage integration processing by the cost matter main line construction module, the cost matter unit data is generated, cross-stage item integration record data is formed by the different-stage item data, and thus a stable main line structure is established at the data level, and consistent organization and centralized management of the cross-stage item data are realized.

This invention discloses a blockchain-based engineering cost management system and method, relating to the field of engineering cost technology. It includes a chain storage stage and a weight adjustment stage. The chain storage stage includes the following steps: the management terminal inputs member information and initializes the weight value of each user terminal; the processing unit establishes a blockchain; the user terminal inputs engineering cost content; and the processing unit executes a dual authentication procedure. The dual authentication procedure performs biometric authentication on members and business knowledge authentication on the input engineering cost content. This invention utilizes the chain storage structure of blockchain to ensure the credibility of engineering cost at the audit level. The dual authentication procedure plus cross-validation procedure can ensure that the person operating the user terminal is the member themselves and can also confirm that the operator understands the internal business of the engineering cost team, improving the authenticity of the engineering cost content. The dynamically adjusted weight values ​​can adapt to different engineering cost teams.

This invention belongs to the field of hydropower project cost management technology, specifically providing a method and system for reusing historical cost data of hydropower projects based on standardized coding. The method includes: constructing a material master data dictionary and assigning corresponding master data codes to each material item; collecting core business data from historical projects, preprocessing and fusing the personnel, materials, and machinery data, and establishing a mapping relationship between the personnel, materials, and machinery data and the corresponding material items in the material master data dictionary based on comprehensive confidence, generating a standardized historical database; constructing project feature vectors for new projects and historical projects based on the standardized historical database, determining the weights of each dimension through a combined weighting method, calculating the comprehensive similarity of projects, and outputting a set of similar historical projects; and reusing historical cost data based on the set of similar historical projects, transforming the historical cost data into project cost data for new projects. This invention can improve the standardization of historical cost data and the efficiency of cross-project reuse.

The invention provides a maintenance project cost management and control method and system based on dynamic generation and a decision tree model, and belongs to the technical field of project management and informationization, and the method comprises the steps: obtaining project quota data, and obtaining a comprehensive unit price through employing a comprehensive unit price dynamic generation algorithm; carrying out dynamic budgeting on the current maintenance item by adopting a cosine similarity algorithm to obtain a unit price corresponding to historical data with the highest similarity, and judging whether the unit price is an abnormal unit price or not; if no abnormity exists, the unit price obtained through calculation is adopted to calculate the maintenance project cost; and if the unit price is abnormal, analyzing the abnormal unit price data by adopting a gradient boosting decision tree model, and accounting the maintenance project cost according to a unit price analysis result. According to the invention, through collection and analysis of historical maintenance project data, dynamic generation and an intelligent matching algorithm are combined, a maintenance plan and budget are optimized, resource waste is reduced, it is ensured that the cost of the maintenance project is controlled within a reasonable range, and unnecessary expenditure is reduced.

The invention discloses a power distribution project cost management and control method, device and equipment, and relates to the technical field of project cost management and control, and the method comprises the following steps: coding a cable, and constructing a cost reference library based on the cable code; based on the cost reference library, carrying out optimization calculation on the cable laying path to obtain the installation cost, and quantifying the uncertainty of future operation loss to obtain the operation loss cost; constructing an optimization target in combination with the installation cost and the operation loss cost, and solving the optimization target to obtain the cable optimal area of each cable section; and correcting the optimal area of the cable based on the construction data. The method is used for solving the problem of poor adaptability caused by incomplete consideration of an existing power distribution project cost management and control model.

This application provides a BIM-based method and system for engineering cost management, relating to the field of engineering cost management technology. The method includes: collecting 3D point cloud data of components at the construction site, combining it with geometric attribute data and cost data from the BIM model to generate engineering cost data and establish cost geometric correlation information; performing geometric analysis on the point cloud data to extract 3D deformation data, and constructing a component relationship diagram based on the BIM model; mapping the deformation data and cost information to the relationship diagram, generating a cost deviation probability distribution through a dual-channel convolutional neural network, and finally using a reinforcement learning algorithm to generate a cost compensation strategy and automatically update the BIM database, thereby achieving dynamic adjustment of engineering costs. This application improves the adaptive control capability of engineering costs under construction geometric deformation scenarios.

The application discloses a BIM and big data-based project cost management system and relates to the technical field of cost management, solves the technical problems of poor adaptability of progress early warning threshold, mutual separation of progress and cost control, inability to accurately trace the progress and cost abnormal causes, and inability to dynamically optimize resource allocation, realizes self-adaptive genetic algorithm through budget cost double-layer intelligent deduction and accurate verification to complete multi-dimensional resource optimal allocation of project manpower, materials, machinery and funds, introduces a similar historical project final account correction factor to complete deviation correction, completes algorithm optimization pricing and historical real scene final account calibration double closed loop cost checking, constructs a visual double line progress dynamic research and judgment system, generates a standard plan cumulative completion rate curve based on a BIM4D time sequence model, links real-time collection of construction data to generate an actual completion rate curve, replaces traditional qualitative progress judgment with quantitative deviation amount, and progress deviation degree can be quantified, intuitively and visually presented.

The invention relates to the technical field of project management, in particular to a BIM-based project cost dynamic adjustment method and system, and the method comprises the following steps: carrying out the linkage budget adjustment based on the number of components and the stage progress change, and carrying out the statistics to generate project cost dynamic data. According to the method, time change analysis of the component number is realized through data mapping of component numbers and time nodes, the reference amount data of various components in the budget structure is combined, the actual influence of the component number change on the budget amount is quantified, a continuous conduction path of budget difference is constructed, and a time sequence response relationship of budget adjustment is defined; dynamic statistics and staged optimization control of project cost are realized by acquiring starting and ending time and change records of a construction stage, analyzing a coverage offset ratio of a plan and actual time, associating budget error response and constructing a linkage relationship between time change and budget adjustment; and the dynamic response capability of project cost management and the accuracy of stage cost prediction are enhanced.

The invention relates to the technical field of project cost management, and discloses a project cost real-time control and early warning method and system based on business and financial integration, and the method comprises the steps: obtaining project business data and financial data; generating a multi-dimensional real-time state vector representing the current running state of the project based on the data; calculating an error vector between the real-time state vector and a preset target state vector; according to the error vector, calculating a parameter adjustment quantity vector through a preset control model; and analyzing the parameter adjustment quantity vector into a management and control instruction or early warning information and outputting the management and control instruction or the early warning information. According to the method, the business and financial data are fused into the quantitative state vector, the quantitative adjustment instruction is calculated by using the automatic control model, an automatic closed-loop management and control mechanism of the project cost is constructed, the defects of data splitting, feedback lagging and decision subjectivity in traditional management are overcome, and the accuracy and timeliness of project cost management and control are improved.

The invention belongs to the technical field of enterprise cost management, and provides an enterprise project cost management method and system based on a dual matching mechanism. Comprising the steps of collecting project data of an enterprise multi-source business system in real time; performing standardized governance on the project data, and extracting project features based on the project data after standardized governance; processing the item features based on a Llambda 3 model, and automatically identifying the item types to obtain an identification result; based on the identification result of the item type, cost collection and distribution are carried out by adopting a differentiation rule; inputting the item features into a Llambda 3 model to obtain a preliminary recognition result, and matching the item features with a preset rule base to obtain a verification result; when the preliminary identification result is consistent with the verification result, the item type is confirmed; and if not, triggering an artificial rechecking process. The problems that in the prior art, project types are divided manually, the cost data quality is poor, the collection rule is rigid, and deep analysis is lacked are solved.

This invention belongs to the field of construction project cost management display technology, specifically a construction project cost management display device. It includes a main board with a display screen embedded in its center. Two sets of display panels are symmetrically mounted on the main board, and two sets of suspension shafts are symmetrically connected to the display panels. Rollers are spun onto the suspension shafts. A limiting frame is provided at the upper end of the main board, which limits the rollers, and the rollers rotate around the limiting frame. Pulling the two sets of display panels in opposite directions separates them, thereby opening the display screen. Because the display screen is embedded in the center of the main board, the risk of the display screen being bumped is reduced. Furthermore, during the pulling process, the display panels drive the suspension shafts and rollers to move together, and the rollers rotate along the limiting frame. The cooperation between the rollers and the limiting frame guides the movement of the display panels. The rotation of the rollers not only makes the movement of the display panels smoother but also reduces wear caused by the movement, thus increasing the service life of the device.

The invention provides a BIM-based budget list intelligent compilation system and method, and relates to the technical field of construction project cost management, and the system comprises a data import module, a project directory construction module, a knowledge graph module, an intelligent matching module, a list processing module and a pricing module. The system is characterized in that the data import module is used for importing a real object engineering quantity file generated by a BIM model or external, and analyzing component related information; the project directory construction module is used for constructing a construction drawing budget project directory structure according to levels; the knowledge graph module is used for constructing and updating a component-list-quota knowledge graph; through intelligent association of BIM component attributes and list specifications and in combination with a rapid retrieval mechanism of a path key value table, traditional tedious operations of manual graph recognition, amount calculation and list association are replaced, the list compiling process is greatly simplified, the compiling progress is remarkably accelerated, the overall period of cost compiling is effectively shortened, and the work propulsion efficiency is improved.

The invention provides a BIM-based engineering cost management method and system, and relates to the technical field of engineering cost management.The method comprises the steps that three-dimensional point cloud data of construction site components are collected, geometric attribute data and cost data in a BIM model are combined, engineering cost data are generated, and cost geometric association information is established; and performing geometric analysis on the point cloud data to extract three-dimensional deformation data, and constructing a component association relation graph based on a BIM model. Deformation data and cost information are mapped into a relation graph, cost deviation probability distribution is generated through a two-channel convolutional neural network, finally, a cost compensation strategy is generated through a reinforcement learning algorithm, a BIM database is automatically updated, and dynamic adjustment of the project cost is achieved. According to the invention, the self-adaptive regulation and control capability of the project cost in a construction geometric deformation scene is improved.

The invention relates to the field of project cost management, in particular to a project cost full-period digital cost prediction system. Comprising a data acquisition module, a topological feature extraction module, a deep learning prediction module, an anomaly detection module, a risk assessment module, a decision support module, a data preprocessing module, a multi-level storage module, a model updating module and a user interface module. Performing topological analysis on the project cost data through a multi-scale complex construction technology, and generating topological feature descriptors reflecting the internal structure relationship of the data; a topology perception neural network architecture is adopted to carry out cost prediction; according to the method, the topological structure difference between new data and historical data is compared based on the persistent coherence theory, early risk early warning is achieved, and the problems that in traditional project cost management, prediction precision is low, risk identification lags behind, and generalization ability is weak are solved.

The invention discloses a construction project cost index analysis system based on big data, and belongs to the technical field of project cost management. The system comprises a data acquisition module, a data processing module, a data analysis module, an index application module and a data security module, and a multi-source data access unit and a data supplementation unit cooperatively acquire project basic data, cost file data and supplementary feature data, so that comprehensive coverage, accurate acquisition and efficient updating of cost data are realized; through structural processing, intelligent automatic matching and a multi-dimensional data correction mechanism, accurate binding of list subitems and indexes is efficiently completed, meanwhile, manual intervention of special scenes is supported, automation efficiency and flexible adaptability are considered, the problems of inaccurate data association and uneven quality are solved, and the data association efficiency is improved. Based on index generation, feature analysis and a diversified application unit, an intelligent application system covering the whole process of the cost is constructed, and the data security guarantee of the cost index is realized in combination with a triple protection design.

The invention discloses a dynamic optimization and multi-dimensional cooperation project cost management method and system, and relates to the field of project cost management. According to the method, full-life-cycle cost general control reference data including transverse professional sub-items and longitudinal stage sub-items are acquired, actual cost data are acquired in real time based on a preset cost general control model, the two data are dynamically associated, engineering changes are classified according to preset rules, and early warning is triggered when deviation exceeds a dynamic threshold value. And finally, decision information is generated according to a key function priority principle. The system comprises a data acquisition, processing and decision module. According to the invention, full-period dynamic management and control and multi-specialty cooperation of the construction cost are realized, and cost controllability and core function priority are guaranteed.

The invention relates to the technical field of research and development cost management, in particular to a science and technology research and development project cost management and control system. The project information module is used for sorting project information; the personnel information module is used for sorting project personnel information; the database module is used for tracing information of projects and project personnel; the retrieval module is used for acquiring information of projects and personnel; the cost statistics module is used for adjusting data of personnel project cost, the storage module is used for uploading flow data of each item of cost to the database module and is traceable, the communication module is used for providing a communication network for the storage module, and the display module is used for displaying a display image processed by the cost statistics module. According to the method, data of the overlapping personnel of the multiple projects can be screened out, the labor proportions of the overlapping personnel of the multiple projects in different projects are analyzed and calculated, the optimal adjustment scheme can be obtained through distribution and evaluation, and the cost is saved.

The invention discloses a project cost evaluation method and device, equipment and a medium. The method comprises the steps of determining basic cost according to resource prediction information of a target project; establishing a cost influence factor experience library according to the historical development data of the historical project, and determining a decision data matrix according to the cost influence factor experience library; wherein column elements in the decision data matrix represent cost influence factors, and row elements represent cost parameters generated by the influence of the cost influence factors; determining an influence weight of each cost influence factor according to the decision data matrix through a grey correlation algorithm based on an entropy weight; and determining a target cost evaluation result according to the basic cost and the influence weight of each cost influence factor. According to the technical scheme, the problems that project cost evaluation is high in subjectivity and the evaluation result is not high in accuracy and reliability can be solved, and accurate and reliable data support is provided for project cost management and project decision making.

The invention relates to the field of supervision project management, and discloses an electric power engineering supervision optimization method and system based on big data, and the method comprises the steps: obtaining the cost static data and the cost dynamic data of the whole life cycle of the electric power engineering; defining a cost event including a raw material price rising event and a raw material price falling event; carrying out association labeling on the cost event and the corresponding process; determining an influence relationship between the raw material price fluctuation and the process cost through an association rule mining algorithm so as to determine an association model of the process cost influence degree; when it is monitored that the real-time price fluctuation of the raw materials forms a cost event, the real-time process cost influence degree is calculated through a correlation model of the cost correlation influence degree; and when the real-time process cost influence degree is greater than or equal to the preset process cost influence degree, generating structured early warning information and pushing the structured early warning information to related supervisors and project responsible persons. The project cost management and control efficiency and effect in electric power project supervision can be improved.