62 results about "Project cost management" patented technology

The invention provides a project cost management method based on artificial intelligence, and relates to the technical field of project cost, and the method comprises the following steps: 1, data mining and analysis: extracting valuable information from a large amount of historical project cost data through building a data mining model, and analyzing the mined data through a data analysis tool; step 2, automatic measurement and pricing; step 3, constructing a cost prediction model; step 4, risk assessment and early warning; step 5, project progress and cost collaborative management; step 6, intelligent cost control; and 7, intelligent supplier management. By constructing the data mining model and using the neural network algorithm to cooperate with the association rule mining algorithm, deep mining can be effectively performed on the engineering cost data, and meanwhile, the data analysis tool is used to analyze the data, so that the workload of data collection is reduced, and the efficiency of engineering cost management is improved.

The invention discloses a project cost risk monitoring method and a project cost management platform, and the method comprises the steps: S1, carrying out the real-time collection and standardization processing of multi-source data: collecting dynamic data in real time through an Internet of Things device at a construction site, carrying out the butt joint of a design drawing, a financial system and the like, obtaining static data, and employing a data cleaning, conversion and integration technology; s2, carrying out risk factor identification and correlation analysis based on a knowledge graph; s3, implementing risk quantitative prediction and early warning driven by artificial intelligence; s4, real-time monitoring and automatic verification of contract performance of blockchain enabling are realized; s5, providing dynamic cost adjustment and optimization decision support; through real-time collection and standardization processing of multi-source data, data islands of all parties participating in a project are broken, and accuracy, integrity and timeliness of key data such as construction progress and cost expenditure are ensured. Based on big data analysis and artificial intelligence prediction, more accurate risk assessment and cost prediction are provided for project managers.

The invention relates to the technical field of project cost management, and discloses a project cost dynamic management method. The method comprises the following steps: marking a timestamp of a data updating node in a historical cost database, extracting a consumption index of each subentry project in a specified interval before and after the timestamp, and constructing a consumption feature set dynamically associated with the cost; inputting the consumption feature set into an optimized neural network, calculating the deviation degree of the same sub-project in the construction stage and the design stage through time sequence comparative analysis, and generating the difference representation of the actual cost and the plan cost; a material price fluctuation coefficient is used as an adjusting variable, a fuzzy comprehensive evaluation model is adopted to carry out multi-dimensional reasoning on the difference representation, and the influence weight value of each cost component on the cost deviation is obtained; key parameters related to the market supply and demand index and the construction progress deviation rate are mined, the key parameters are input into a pre-trained evaluation model, a screening threshold value is dynamically adjusted according to a model output numerical value, and core parameters with influence weight values higher than the adjusted threshold value are screened out.

The invention relates to the technical field of construction industry project cost, and provides a project cost management system based on big data, the core of the system is to integrate a big data technology and comprehensively manage project cost, data management covers links of acquisition, storage, analysis and maintenance, data quality and safety are ensured, and a foundation is built for cost management; the accurate cost analysis uses multiple algorithm models to deeply mine data association, so that accurate prediction and fluctuation reason analysis are realized, and cost optimization is assisted; the efficient business logic layer and the user interaction layer cooperatively operate, the business function is complete, the process is smooth, the interface is friendly, the visualization is strong, and a feedback channel is arranged to promote optimization; data acquisition is wide, storage is efficient, and the method is far better than a traditional scheme; the analysis depth and the visualization effect are prominent, and a more valuable decision basis is provided; the system is complete in business function and scientific in management, improves enterprise cost control and decision-making capability, and is good in user experience and high in safety.

The invention relates to the technical field of project cost management, in particular to a hydraulic engineering construction cost control system and method, and the system comprises a material consumption analysis module, an inventory early warning calculation module, a dynamic inventory adjustment module, a replenishment trigger optimization module, and a consumption stability evaluation module. According to the method, the material consumption rate is dynamically monitored, the construction progress and engineering quantity are combined to measure and calculate data, a consumption trend curve is established, the actual use condition is compared, the consumption rate deviation is accurately quantified, real-time evaluation of material use is achieved, the number of supply days is calculated in combination with inventory data, the replenishment period is matched, and the replenishment time is dynamically adjusted; the inventory level is optimized, fund occupation is reduced, the stability is evaluated according to the consumption fluctuation range, the maximum consumption fluctuation value is calculated, the demand is adjusted in combination with replenishment, the inventory early warning threshold value is dynamically corrected, the supply chain breakage risk is reduced, the adaptability of construction material management is improved, and the cost control accuracy is improved.

The invention relates to the technical field of project cost consultation management, and discloses a project cost consultation management method and system, and the method comprises the steps: building a material price database which is dynamically updated in real time, obtaining market material price data from the Internet, and updating the material price database; adding the material price database into the data warehouse set, executing a cluster cache strategy, and optimizing the data warehouse set by using cache; executing a load balancing strategy on the server network of the transmission data warehouse set; acquiring data features of the cost project, executing an intelligent matching strategy, and acquiring an optimal cost model of the cost project; calculating the cost of the cost project by using the optimal cost model; if the cost is higher than the cost threshold, executing a budget project adjustment strategy, and adjusting budget distribution of sub-projects of the cost project; and executing the block chain recording strategy, and storing the operation record in the log record. And the reliability and accuracy of project cost management are improved.

The present invention discloses a quality control management system for project supervision, which relates to the technical field of project management, and includes a control management platform, wherein the control management platform is communicatively connected with a project information management module, a project progress management module, a project cost management module, a quality inspection and evaluation module, a project quality grading module, and a resource allocation management module, wherein the modules are electrically connected; the project information management module is used to clarify the quality control objectives of the project. The quality control management system for project supervision ensures that the project reaches the predetermined quality standards in each link by setting the quality grade standard and the evaluation process, and conducts a comprehensive and objective evaluation of the project quality through quality inspection and evaluation, quality evaluation coefficient calculation, and quality grade determination steps, thereby timely discovering and solving potential quality problems, so as to improve the reliability and safety of the project.

The invention relates to the field of cost management, in particular to a software project cost management method and system based on big data. A software project cost management system based on big data comprises an entity word annotation module, a word embedding operation module, a function module query module and a software cost prediction module. According to the method, the function demand tag, the non-functional demand tag and the technical demand tag are determined according to the software development demand document of the user, and the function module correspondingly required by the software development demand document is determined according to the function demand tag; based on the determined function modules, selecting the closest function module from a function module library consisting of software projects of which the software design is completed, further determining cost information, and selecting the closest software project from the function module library to determine repeated workload to correct the cost information; finally, automatic software cost information prediction is completed, and reference is provided for contract pricing of a software development company.

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 an intelligent engineering cost investment control system and method fusing multi-source data, and relates to the technical field of engineering cost management. The system comprises a data acquisition module, a data preprocessing module, a multi-source data fusion module, an intelligent decision module and a cost control execution module. The data acquisition module is used for extracting geometric, material, quantity, construction process and time parameters of the components from the BIM model; the data preprocessing module eliminates noise and unifies formats; the multi-source data fusion module constructs a fusion feature matrix; the intelligent decision-making module performs deep feature mining through an improved convolutional neural network and outputs an accurate cost prediction result; and the control execution module executes multi-stage regulation and control according to the deviation between the predicted cost and the target cost. Accurate prediction and dynamic control of the project cost are realized, and scientificity and effectiveness of project cost management are improved.

The invention provides a construction project cost management method and system based on big data, and relates to the field of project cost management, and the method comprises the steps: obtaining project cost data, and carrying out the preprocessing of the project cost data, so as to obtain a project cost data set; the project cost data set is converted into a standard project cost data set meeting the unified standard, multi-dimensional data verification is carried out to obtain a multi-dimensional verification result, and the data fluctuation degree of the standard project cost data set is calculated to obtain a data fluctuation rate; constructing a data quality evaluation model and performing quality evaluation on the standard project cost data set to obtain a quality score of each data point; according to the quality score of the standard engineering cost data obtained in real time and a preset threshold value, when the quality score of the standard engineering cost data does not meet the preset threshold value, an early warning mechanism is triggered. The method is used for overcoming the defect that the processing speed is low when an existing data quality control technology is used for processing large-scale data.

The invention relates to the technical field of cost management, in particular to an intelligent engineering cost management method and system based on big data, and the method comprises the following steps: collecting task progress materials, equipment and working hours, carrying out the alignment standardization, extracting cost factors, generating a cost parameter set, calculating a multi-parameter trend difference, recognizing risk linkage, and generating risk propagation data; the method comprises the following steps: acquiring construction task progress materials, analyzing a relationship between parameter changes and budget expenditure to form a budget influence path, calculating a difference value threshold exceeding mark abnormal cumulative weight, and comparing budget deviation with a factor direction to generate a project cost management result. The method comprises the following steps: extracting cost influence factors, calculating trend difference, identifying risk linkage, analyzing a relationship between parameter change and budget expenditure to form an influence path, calculating difference value over-threshold marking abnormity and accumulating weight, comparing budget deviation and factor fluctuation direction to adjust items, realizing cost dynamic monitoring and accurate control, and improving budget execution and risk response efficiency.

The invention relates to the technical field of building information model application, in particular to a fabricated building informatization construction method and system. According to the method, the BIM design model is constructed, the component information is obtained, the construction progress plan and the BIM design model are associated, the component production plan is obtained, the purchase plan is made according to the component production plan, and the project cost is estimated. And then obtaining the actual cost of each stage according to the project period, designing a deviation threshold value, judging that the cost deviation is unreasonable when the deviation value of the actual cost of the stage and the estimated project cost reaches the deviation threshold value, and predicting the cost change of the subsequent stage of the project according to historical data and the raw material price change. And finally, the purchase plan and the component production plan are adjusted according to the prediction result, and the project cost is estimated again. Through the scheme, the whole-process monitoring and adjustment of the assembly building cost can be effectively realized, and the accuracy and efficiency of project cost management are improved.

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 discloses an intelligent cost compilation and auditing method based on artificial intelligence in a communication network, and the method comprises the steps: carrying out the dynamic evaluation of network resources based on a multi-service demand analysis model, generating an optimized resource distribution scheme according to an evaluation result, carrying out the intelligent compilation of cost through a deep learning algorithm, and carrying out the auditing of the cost. Automatically auditing the compiled cost to ensure the rationality and accuracy, and adjusting a resource allocation strategy based on an auditing result; according to the intelligent cost compiling and auditing method based on artificial intelligence in the communication network, the problem that in the prior art, under the condition that multiple service requirements coexist, resource allocation is unbalanced in the method is solved, specifically, when multiple projects or tasks are carried out at the same time, the system cannot effectively process all the requirements due to unreasonable resource allocation, and the system is not easy to carry out. The resource allocation problem may cause reduction of service quality, and further affects the overall efficiency of project cost management and user experience in a communication network construction process.

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 present invention relates to the technical field of electrical digital data processing for buildings, and more specifically to a method and system for construction project cost management based on electronic information technology. The method comprises: obtaining a building information model corresponding to a target building, the building information model being established based on the target building's engineering electronic information; extracting load transfer paths and load values ​​from the building information model, and establishing a load transfer tree diagram for multiple components within the target building based on the load transfer paths and load values; analyzing the impact of thickness changes of components corresponding to each node in the load transfer tree diagram on components corresponding to other nodes within a preset range, and determining thickness change evaluations corresponding to each component; determining adjusted thicknesses for each component based on the thickness change evaluations corresponding to each component, and optimizing the construction cost of the target building based on the adjusted thicknesses. In the present invention, by processing the electrical digital data of the target building, the balance between safety and economy in construction project cost management is improved.

The invention relates to the technical field of project cost management, in particular to a construction engineering cost management system which comprises a stage boundary module, a stage characteristic fitting module, a global parameter optimization module, a double-layer dynamic inference module and a real-time adaptation adjustment module. According to the method, the accuracy of stage division is improved by extracting the single-stage construction period consumption and the stage cost ratio and combining calculation of the slope and the inflection point and accurately recognizing the stage demarcation point, the definition of segmented data is enhanced through cost change rate difference calculation and stage boundary point marking, and the accuracy of stage division is improved. On the basis of calculation of the ratio of resource investment to stage cost increment, the fitness of a cost trend model is optimized, smoothness and accuracy of the overall cost trend are achieved through global error extraction and demarcation point adjustment, dynamic prediction is combined with segmented cost volatility and newly-added data, the accuracy and timeliness of the cost prediction range are optimized, and the cost prediction efficiency is improved. And calculating the construction period consumption and the cost increment deviation value in real time, and dynamically adjusting the trend parameters.

The invention relates to the technical field of building construction management, and discloses a building outer wall construction cost prediction and control system based on big data analysis, and the system comprises a data collection module, an analysis engine, a decision support module and a visualization module. The core method comprises the following steps: calculating a construction behavior entropy based on high-frequency dynamic data collected from a construction site through an analysis engine so as to quantify the disorder degree of an operation process; a cost potential energy model is established in combination with the construction behavior entropy and the external environment constraint and is used for quantifying the risk of actual cost hyper-branched in the future; and constructing a conduction network based on a working decomposition structure (WBS) to predict an evolution path of the risk, and diagnosing a systematic source by identifying resonance between behavior entropies of different dimensions. According to the method, dynamic quantification, predictive identification and root diagnosis of cost risks can be realized, passive control is changed into active intervention, and the perspectiveness and the refinement level of project cost management are remarkably improved.

The invention discloses a power grid project cost management system based on a cloud platform, and relates to the technical field of project cost management, and the system comprises an information acquisition and analysis module, a scheme analysis module, a scheme decision module and a project uploading module. Scientific data basis is provided for project budget and cost control of the target project, market information is acquired in the construction process of the target project, each construction adjustment scheme is formulated based on the change of the market information, and each construction adjustment scheme is selected based on the specific construction progress of the target project, so that smooth completion of the target project is ensured, and the construction efficiency is improved. And finally, after the target project is completed, the project information of the target project is uploaded to the cloud platform to serve as a project reference for construction of the next project, so that convenience and flexibility of power grid project cost management are ensured.

The invention relates to an amphibious multi-business and multi-mode complete-period construction project cost management and control system. The system comprises a project income management module, a project budget management module, a project planning management module, a project cost management module, an economic activity analysis module and an assessment and evaluation module. According to the invention, big data, artificial intelligence, mobile internet and other informatization technologies are applied to perform full-business process management and control on project income, budget, planning, cost and economic activity analysis, and by means of dynamic assessment and evaluation, the cost management and control requirements of construction projects of different types, different stages and different conditions are met, so that the cost management and control requirements of construction projects on water or land are met. The cost management and control requirements of the project can be met whether a standard project or an EPC project, the universality of the system is improved, meanwhile, a data flow mechanism with data communicated layer by layer is constructed through strict system logic, the reuse rate of process achievements is improved, the burden of data filling and reporting can be reduced for first-line project management personnel, and the working quality and efficiency are improved.

The present invention discloses a construction cost management system based on BIM and big data, relates to the technical field of construction cost management, and comprises a management terminal, wherein the management terminal is communicatively connected with a cost data acquisition module, a data processing and analysis module, a BIM module and a cost formulation module; the cost-related data of several data sources are acquired through the cost data acquisition module, and are adjusted according to the acquisition load of the cost-related data, thereby generating a cost data set; the data processing and analysis module acquires the cost data set and generates sub-data sets of different visualization progress after processing, and performs data analysis, thereby generating a corresponding BIM building information set; the BIM building information set is acquired through the BIM module to construct a BIM model, and the BIM model is expanded; the BIM model after the model expansion is read through the cost formulation module, and preliminary cost information is acquired through the data reading, and then cost is formulated according to the preliminary cost information, thereby realizing construction cost management.

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.

The application relates to the technical field of engineering project management, in particular to an engineering cost consulting business management method and system, terminal equipment and a storage medium. The method comprises the following steps: if the data completeness degree corresponding to cost data does not conform to the cost task completeness degree standard corresponding to a project cost management task, stopping data processing operation and outputting the data vacancy item corresponding to the cost data; if the data completeness degree conforms to the data matching degree standard corresponding to the project cost management task, judging whether the data matching degree of the cost data conforms to the data matching degree standard; if the data matching degree does not conform to the data matching degree standard, matching corresponding target cost data according to the data matching degree standard, and taking the target cost data as updated cost data; and if the data matching degree conforms to the data matching degree standard, generating a cost achievement report of a corresponding engineering project category according to the cost data. The engineering cost consulting business management method and system, terminal equipment and storage medium provided by the application have the effect of improving the standardization of corresponding data processing of engineering cost consulting business.

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.

The utility model belongs to the technical field of tool boxes, and particularly relates to a project cost management budget tool box which comprises a box body and a hinged box cover, the other end of the hinged position of the box body and the box cover is provided with a hasp for fixing, and the two sides of the box cover are rotationally connected with extension plates through damping rotating shafts respectively. A writing assembly is installed on the extension plate, the box body and the box cover, the writing assembly comprises two U-shaped limiting frames and sliding grooves, and the limiting frames penetrate through the extension plate; the top of the box cover can be used for writing, and the extending plate is kept horizontal by rotating the extending plate upwards and inserting the limiting frame into the clamping groove, so that the writing range is expanded.

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.