41 results about "Cost assessment" patented technology

The invention relates to the technical field of building surveying and mapping, in particular to a high-precision building surveying and mapping method and system, and the method comprises the steps: collecting a point cloud model and an image of a to-be-surveyed building, segmenting the point cloud model into point cloud regions, obtaining the difference coefficient of each point cloud region, recognizing each building region, and removing the point cloud data outside the building region. Performing hole filling on the removed point cloud model; obtaining each structural surface of each building area, obtaining discrete coefficients of each boundary point and each non-boundary point of each structural surface, and screening each noise suspected point from all the non-boundary points of each structural surface; and obtaining a reliability coefficient and a point cloud distortion coefficient of each building area, performing denoising processing on the point cloud data of each building area, and obtaining a three-dimensional model of the to-be-mapped building. According to the method, the denoising precision of the point cloud data is improved, the precision of the three-dimensional model is improved, and therefore more accurate and more visual data support is provided for subsequent building surveying and mapping and project cost evaluation.

An equipment system optimization method driven by deep reinforcement learning comprises the following steps: sequentially constructing an equipment system architecture model and a combat scene simulation model based on a DoDAF framework, then carrying out parameter space sampling in the equipment system architecture model by using a uniform design method, and according to capability items and equipment elements defined by the equipment system architecture model, carrying out parameter space sampling on the equipment system architecture model; constructing a combat effectiveness evaluation model and a system cost evaluation model for evaluating the system; constructing a parameter-modulated deep reinforcement learning (PM-DRL) model to explicitly embed system parameters into an agent state space, and performing data collection and evaluation through the trained PM-DRL model to obtain lt; system parameter-evaluation result gt; a data set; and finally, constructing an optimization model by taking the agent model as a target function, and determining an optimal solution, namely system parameter configuration, by combining the solved Pareto frontier with the preference of a decision maker. According to the method, under the same combat effectiveness requirement, system parameter configuration with lower construction cost can be obtained through optimization.

The present application belongs to the technical field of energy storage economic benefit evaluation, and aims to provide support for new energy storage investment strategies for the future form of power grids. Specifically, a whole life cycle cost evaluation method of energy storage technology suitable for multi-dimensional scenarios is provided, which comprehensively evaluates the economy of different energy storage technologies. The method considers multiple life cycle cost factors such as capital expenditure, operating cost, end-of-life cost and charging cost, and combines energy power ratio (E / P), terrain adaptability and different power application scenarios to simulate and quantify the uncertainty of cost parameters using a Monte Carlo prediction model, and predict the future trend of energy storage technology cost. Finally, intuitive evaluation is performed through detailed cost analysis and the constructed superimposed visualization method. The present application provides scientific decision support for power system planning and energy storage technology investment, and has significant practical value and theoretical significance.

This invention discloses a rapid cost assessment method for engineering changes based on a knowledge graph, comprising: S1, synchronously collecting multi-source heterogeneous data for entity extraction and relation alignment to construct an engineering knowledge graph; S2, inputting change instructions, using a bidirectional graph neural network to identify initial nodes and generate a change impact subgraph; S3, introducing an improved dynamic hierarchical graph attention network with a spatiotemporal decay dependency mechanism, constructing a dynamic decay factor to weight and encode features at each level, and outputting a change feature vector; S4, calling quota standards for cost mapping, performing difference calculation and automated splitting, and outputting a basic cost dataset; S5, combining historical change database similarity matching, and outputting corrected estimated values ​​after deviation calibration and nonlinear correction; S6, encapsulating and generating an assessment report and writing it back to the knowledge graph archive. This invention achieves deep analysis of change propagation paths and refined dynamic cost estimation, improving assessment efficiency and accuracy.

The invention provides an unmanned aerial vehicle routing inspection method and system based on semantic guidance and an asset value cost graph, and the method comprises the steps: reasoning a possible distribution region of a target when the target is not directly observed through analyzing the structure law of semantic information, such as an equipment number, a function partition identifier and the like, in a transformer substation; generating a confidence map to guide the unmanned aerial vehicle to efficiently inspect; constructing a semantic cost graph fusing the static asset value and the dynamic operation risk, and quantifying potential loss of different regions when collision or falling occurs; according to the real-time health state of the unmanned aerial vehicle, semantic guidance is emphasized during normal inspection through a dual-guidance function fusion and switching mechanism, and the unmanned aerial vehicle is automatically switched to asset value cost minimization guidance in an abnormal or emergency state to realize safe disposal; the system adopts a framework of semantic reasoning, cost evaluation and flight control module decoupling, and guidance intelligence and control reliability are ensured. According to the invention, the inspection blindness of the unmanned aerial vehicle is obviously reduced, and the abnormality handling risk is reduced.

This invention belongs to the field of demolition cost assessment technology, specifically disclosing a method for assessing railway route selection and land acquisition costs based on a big data model. The method includes the following steps: constructing a graphical database and a core land acquisition database; acquiring policy-related land acquisition documents and dynamic data for the target area; creating an external database; identifying key factors affecting land acquisition costs; constructing a big data prediction model for land acquisition costs; training the model; and integrating it into a railway route selection design system. When inputting or modifying route plans in the route selection design system, the system calls the big data prediction model for land acquisition costs in real time. Based on the geometric parameters and spatial location of the route, it dynamically calculates and feeds back the corresponding land acquisition cost prediction results, adjusting the route plan until cost control requirements are met. This technical solution achieves dynamic and accurate assessment of land acquisition costs through the deep integration of multi-source heterogeneous databases and a big data prediction model.

The invention belongs to the technical field of rail transit cost assessment, and particularly relates to a rail transit project cost intelligent assessment method based on big data, which comprises the steps of inputting a cost file of a project to be assessed, including sub-items, a list, a quota and labor, material and machine information; performing index physical examination early warning, matching historical sample data, rejecting abnormal values through quartile, calculating a confidence interval, and detecting cost deviation; checking the features, comparing with a standard feature configuration library, and verifying the integrity and normalization of the engineering features; through cooperation of index physical examination early warning and feature examination, the problem of engineering type recognition errors can be quickly responded, so that the defects of a static model are overcome, construction cost files with engineering type labeling errors can be quickly responded, the false alarm frequency can be reduced, and the defects of the construction cost files can be quickly analyzed based on a multi-stage examination mechanism. Compared with manual checking, the method and the device have the advantages that the speed and the efficiency are higher, and the checking is more comprehensive.

The invention discloses a multi-sensor fused intelligent waste steel sorting system, and relates to the field of industrial automation. A central processing module; and a sorting execution module. According to the method, the component proportion and the three-dimensional space distribution characteristics of the whole scrap steel are synchronously collected through a multi-sensor fusion framework, accurate quantification of the economic value of the scrap steel is achieved in combination with a dynamic value scoring formula, and a three-way sorting mechanism is driven based on a scoring threshold value; the problems of cost evaluation distortion and sorting decision disjunction caused by local sampling in the prior art are effectively solved, the reprocessing energy consumption is reduced while the high-value metal recovery rate is increased, the reliability and traceability of the sorting process are guaranteed through a redetection buffer area and a block chain evidence storage mechanism, and finally the maximum utilization of waste steel resources is achieved.

This invention relates to the field of vehicle insurance claims management technology, and discloses a method, system, electronic device, and storage medium for constructing a life table for vehicle insurance claims. This invention integrates internal claims data with external industry data to construct a vehicle damage cost model and a personal injury cost model, and collects data and operational trajectories from the entire claims process. It combines cost deviation calculation and multi-dimensional personnel information to construct a claims personnel profile model, applies the evaluation results to personnel management, and iteratively optimizes based on feedback data. Simultaneously, it utilizes cost assessment and personnel profile correction to generate a graded evaluation of the institution's claims capabilities. This solves the problems in traditional vehicle insurance claims such as the lack of a unified quantitative cost standard leading to significant differences in loss estimation, the single dimension of personnel assessment making it difficult to accurately identify high-risk personnel, and the reliance on macro indicators in institutional evaluation failing to pinpoint micro-level shortcomings. It achieves improvements in the quantitative assessment of case cost, accurate identification of personnel risks, and scientific grading of institutional capabilities in vehicle insurance claims life table pricing.

This application provides an automatic cost assessment method, system, medium, and product for petrochemical software projects, relating to the field of artificial intelligence technology. In this method, the cost assessment system utilizes a large language model to perform preliminary function point identification on project documents and retrieves the names of the preliminarily identified function points using a petrochemical industry knowledge base, supplementing it with professional information such as scale and complexity from historical projects. Then, the cost assessment system iteratively corrects the function point information through interaction between the retrieved information and the preliminary function point list. Finally, the cost assessment system determines the complexity level of each function point, calculates the adjusted number of function points based on the project complexity, and then calculates various cost information and generates an assessment report based on the adjusted number of function points and a project parameter library. This method combines the preliminary identification using a large language model with professional information from an industry knowledge base, improving the accuracy of function point identification through iterative correction, thereby enhancing the reliability of cost assessment.

The invention discloses an AI intelligent agent-based test verification evaluation method and a related device, and relates to the technical field of computers, the method comprises the following steps: carrying out structured segmentation on a test evaluation document based on a father-child segmentation mode to obtain a double-layer segmentation structure document; and vectorizing the contents of the sub-blocks to generate a vectorized knowledge base. And calling a data extraction agent based on a data extraction rule, taking a test data management software database as a data source, and extracting test plan, implementation and result information from the document by using a large language model. And based on a test verification evaluation task planning agent, vectorizing user evaluation requirements, and calculating semantic similarity in combination with a vectorization knowledge base to obtain related evaluation algorithm description and test cost accounting standards. And according to the description and the standard, evaluating test verification process sufficiency, progress and cost based on the test verification sufficiency, progress and cost evaluation agent to obtain a test verification evaluation result. The method can quickly obtain the evaluation result, and supports the leader decision.

The invention relates to a vehicle (1) that is at least partially automated, comprising a computing unit (3) for determining an optimal route between a starting node and a destination node using an A* search algorithm for cost determination based on a plurality of distance-based costs.In a vehicle that significantly reduces the computational effort required to plan an optimal route for at least partially automated driving, the computing unit (3) for planning a trajectory of the vehicle (1) using a modified A* search algorithm comprises an analysis unit (5) which evaluates characteristic parameters of the vehicle (1) at predecessor nodes from a trajectory history, which characterize dynamic influences, and a trajectory determination unit (7) which, together with the distance-based costs, evaluates the costs caused by the dynamic influences of the vehicle (1). The computing unit (3) is designed to control actuators (9) for longitudinal and lateral control of the vehicle (1) such that the vehicle (1) follows the trajectory determined by the modified A* search algorithm.

This application relates to the field of advertising placement control technology and discloses an advertising precision placement method based on recommendation algorithms. The present invention constructs a time-segmented placement state quantity around the current placement cycle, and on this basis, combines the state sequence of similar time periods in history to recursively represent subsequent placement opportunities. Then, it incorporates the unit budget immediate revenue index of the current candidate placement action, the subsequent unit budget revenue index, and the current audience reach saturation level into the placement opportunity cost assessment. Finally, under the constraint of the upper limit of the allocable budget for the current time period, it generates an advertising placement strategy. This unifies the previously fragmented conversion ranking, budget advancement, and audience reach control into the same processing chain. It can not only avoid the excessively rapid consumption of the initial budget and the loss of revenue opportunities in the subsequent time period caused by placing ads based solely on the current conversion probability estimate, but also reduce the risk of revenue decline caused by continuing to place ads after the audience reach saturation.

A multi-variety processing group line opportunity maintenance system considering quality reliability coupling comprises a data acquisition and degradation parameter estimation module, a comprehensive cost evaluation module, a baseline preventive maintenance plan generation module and a fault detection and opportunity maintenance decision module. According to the method, the comprehensive cost in multiple aspects of the production process including the product quality is quantified, a preliminary preventive maintenance (PM) plan is firstly generated on the basis of the production schedule, and then the optimal opportunity maintenance strategy is obtained by taking the total cost in an opportunity window as a target function under the sudden fault situation. And analyzing a system performance evolution rule before and after maintenance, thereby remarkably improving the accuracy and economy of a maintenance decision.

The invention discloses a project cost information management method based on industrial big data, and relates to the field of project information management.The method comprises the steps that to-be-evaluated project information is matched with an internal database and an external database, and historical internal reference data and historical external reference data are obtained; comparing the historical internal reference data with the historical external reference data in the same time period to obtain an overall difference and an individual difference; if the total is not different from the individual, performing project cost assessment on the to-be-assessed project information based on a big data technology to obtain a to-be-invested amount; if the total is not different but the individuals are different, determining a mutual relation between individual difference items, and performing project cost evaluation on the to-be-evaluated project information according to the mutual relation to obtain a to-be-invested amount; and if so, performing project cost assessment on the to-be-assessed project information according to the credibility of the database to obtain a to-be-invested amount. The method has the effect of improving the accuracy of the evaluation result.

The invention discloses a main network construction cost rapid auxiliary review method and system, and the method comprises the steps: firstly obtaining construction cost data information and construction cost budget information of a main network construction cost, and recognizing each construction cost demand type and construction cost data distribution information based on the construction cost data information; then, based on the cost budget information, identifying a cost list, and based on the cost data distribution information and the cost list, identifying cost evaluation index values and cost evaluation reasons; then, based on the cost evaluation index value and the cost evaluation reason, identifying a cost evaluation result, and based on the cost evaluation result, generating main network auxiliary evaluation information of the main network cost; according to the method, the cost evaluation result of each cost demand type is comprehensively analyzed, workers are assisted to comprehensively analyze each cost demand type, and each cost demand type is comprehensively analyzed through the evaluation index, so that the timeliness, the accuracy and the comprehensiveness of main network cost evaluation analysis are improved, and the efficiency of main network cost evaluation analysis is improved. And meanwhile, the review efficiency is further improved.

The invention discloses a system for engineering cost big data analysis and intelligent decision support, and relates to the technical field of construction engineering cost assessment, and the system comprises an Internet of Things collection terminal which is used for collecting geographic information data of each building area; the sensor is used for collecting structural data of each structural member of the building in each building area; the server is used for collecting material supply chain data; the processor is used for obtaining geographic risk data of the building area through nonlinear calculation according to the geographic information data; and according to the structure data and the geographic risk data of the building area where the building is located, outputting a structure data predicted value at the beginning moment of the project through a neural network. According to the scheme, the supply coefficient and the dynamic priority calculation mechanism are introduced, objective engineering loss evaluation is combined with a subjective strategy, so that the material scheduling efficiency is optimized, and the problem of resource waste caused by single supply demand judgment in the prior art is solved.

The present invention relates to the technical field of fishery cost management, specifically a real-time data collection method and system for intelligent cost accounting of marine fisheries, which obtains ship operation positioning data to calculate the speed change rate, screens stable periods to reconstruct operation sections, matches fuel records to analyze flow and level to calculate fuel consumption, combines wind speed, ocean current, and tide level to analyze disturbance direction to divide interference levels, and integrates time, location, behavior type, fuel consumption, and interference level to construct index splitting entries. The present invention identifies continuous operation intervals through speed change rate, combines fuel level and flow data to cross-validate and screen effective fuel consumption, and reduces statistical deviations. Through the dynamic mapping of equipment operating parameters and energy consumption output, a refined splitting of operation behavior and energy loss is achieved, and the ability to identify abnormal working conditions is improved. Environmental parameters such as ocean current and wind speed are introduced to calculate the combined force of disturbances, quantify the actual impact of natural conditions on energy consumption, and correct cost assessment errors.

An information processing apparatus includes a cost evaluation unit and a correction processing unit. The cost evaluation unit evaluates a correction residual after crosstalk correction processing as a cost. The correction processing unit performs a plurality of different pieces of crosstalk correction processing while determining a correction range and a correction amount based on the cost.

The application relates to the technical field of building surveying and mapping, in particular to a high-precision building surveying and mapping method and system. The method comprises the following steps: collecting a point cloud model and an image of a building to be surveyed and mapped, segmenting the point cloud model into point cloud regions, obtaining difference coefficients of the point cloud regions, identifying building regions and removing point cloud data outside the building regions, and performing hole filling on the removed point cloud model; obtaining structure surfaces of the building regions, obtaining discrete coefficients of boundary points and non-boundary points of the structure surfaces, and screening noise suspected points from all the non-boundary points of the structure surfaces; obtaining reliable coefficients and point cloud distortion coefficients of the building regions, performing noise removal processing on the point cloud data of the building regions, and obtaining a three-dimensional model of the building to be surveyed and mapped. The application aims to improve the noise removal precision of the point cloud data and the precision of the three-dimensional model, thereby providing more accurate and more intuitive data support for subsequent building surveying and mapping and engineering cost assessment.

This invention discloses a method and system for international engineering cost analysis and control. The cost analysis and control method includes the following steps: S1, collecting international subcontractor data, material supply chain data, cross-border environmental data, and project engineering data, and standardizing the above data to obtain standardized data; S2, analyzing and evaluating the standardized data to obtain subcontractor cost assessment results, supply chain cost analysis results, and cross-border cost risk analysis results; S3, combining the subcontractor cost assessment results, the supply chain cost analysis results, the cross-border cost risk analysis results, and the standardized data obtained in step S1 with timestamps to package them into a cost control block, and uploading it to the blockchain for notarization. This invention provides a method and system for international engineering cost analysis and control, which achieves accurate control of international engineering costs by collecting and analyzing relevant data.

This application discloses an AI-based experimental verification and evaluation method and related apparatus, relating to the field of computer technology. The method includes: structurally segmenting experimental evaluation documents based on a parent-child segmentation pattern to obtain a two-layer segmented document structure; vectorizing the content of its sub-blocks to generate a vectorized knowledge base; invoking a data extraction agent based on data extraction rules, using an experimental data management software database as the data source, and extracting experimental plan, implementation, and result information from the document using a large language model; vectorizing user evaluation needs based on an experimental verification and evaluation task planning agent, calculating semantic similarity using the vectorized knowledge base, and deriving relevant evaluation algorithm specifications and experimental cost accounting standards; and evaluating the sufficiency, progress, and cost of the experimental verification process based on the specifications and standards using an experimental verification sufficiency, progress, and cost evaluation agent to obtain the experimental verification evaluation results. This application can quickly obtain evaluation results, supporting leadership decision-making.

This invention discloses a method for quantitative analysis and evaluation of software function points based on concept understanding, relating to the fields of software engineering and cost assessment. The method includes the following steps: standardizing and preprocessing the original software requirements document to generate a structured dataset labeled with function point tags; constructing a hierarchical prompting engineering framework based on the structured dataset, performing two-stage function point reasoning using a large language model, and outputting an initial function point list; post-processing the initial function point list, including format validation and semantic disambiguation, to generate a standardized function point list; and evaluating model performance using multi-dimensional quantitative indicators based on the standardized function point list, and dynamically optimizing the prompting engineering framework and model reasoning process based on the evaluation results. This method improves the automation level, consistency, and accuracy of the software function point analysis process through concept-guided intelligent reasoning, quantitative closed-loop evaluation, and standardized post-processing.

This application discloses a real-time engineering cost assessment and early warning system based on multi-source data fusion and dynamic learning, comprising: a multi-source data acquisition module for collecting construction process data, historical project data, market data, and design drawing data; a preprocessing module for preprocessing and fusing the collected multi-source data to form a multi-dimensional feature vector with a unified timestamp; a hybrid neural network assessment module for inputting the multi-dimensional feature vector into a pre-constructed hybrid neural network model for cost assessment; a dynamic optimization learning module for online learning and dynamic optimization of the hybrid neural network assessment module based on a transfer learning strategy; a blockchain storage module for storing key data generated during the assessment process; and a progress monitoring and early warning module for real-time monitoring of construction progress, calculating progress deviations, and triggering corresponding early warnings. This system achieves accurate assessment, real-time early warning, and dynamic optimization of engineering costs.

This invention discloses a BIM-based method and system for cost assessment and management of building construction projects. By acquiring building construction feature data, a multi-scale graph-time series fusion prediction model is established. The spatial relationship channel uses an HGAT hierarchical graph attention network to aggregate spatial features layer by layer, while the temporal evolution channel utilizes a TCN temporal convolutional network to capture the time features of cost accumulation. A cross-modal attention mechanism is used to adjust the weights of spatial and temporal features. The building construction feature data is input into the multi-scale graph-time series fusion prediction model. Based on the predicted project cost, a judgment is made. When the actual project cost exceeds the predicted cost, an attribution mechanism based on SHAP values ​​and counterfactual reasoning is triggered to generate a quantifiable optimization scheme. This replaces traditional manual calculation and experience-based judgment, significantly reducing manpower input and shortening the cost assessment cycle.

The invention relates to the technical field of engineering cost, in particular to a road engineering cost assessment management system and method. The method comprises the following steps: firstly, inputting the road size and road data of a to-be-built asphalt road into a system through a drawing input module and a road data input module; and secondly, the asphalt road cost analysis module analyzes the asphalt road cost according to the road size and the road data to obtain the cost data of the base layer, the bottom layer and the surface layer of the asphalt road. And then, the asphalt road cost evaluation module obtains an asphalt road cost evaluation result according to the cost data. And finally, outputting the asphalt road cost evaluation result through an output module. According to the road engineering cost evaluation management system and method, the cost evaluation result of the asphalt road can be effectively improved.

The invention discloses a high-altitude wind-resistant photovoltaic support cost prediction model which comprises an initial parameter acquisition module, an uncertainty risk modeling module, a collaborative optimization engine module, a final scheme generation module and a decision support output module. According to the method, reference cases are accurately matched through structural feature vectors and cosine similarity, and long-term uncertainty risks such as steel prices and extreme weather are quantified by applying a financial engineering-level probability model, so that static cost evaluation is improved into dynamic full-life-cycle cost probability prediction; a risk weighted cost adaptability function fused with a foreground theory is constructed, and a topological optimization algorithm is driven to actively avoid a structural form with high potential cost in iteration. Therefore, the method not only can generate an optimization structure which systematically avoids the full-life-cycle risk, but also can provide quantitative decision support, so that the total cost of ownership of a project is remarkably reduced at the source of design, and the investment value and the market competitiveness of the project are comprehensively improved.

The invention relates to a computer-implemented method (2) for motion planning for a vehicle (1), wherein the following steps are carried out in each of a plurality of calculation cycles: providing (21) state information relating to the vehicle (1) and environment information relating to an environment of the vehicle (1); defining (22) multiple possible maneuvers (M1, M2, M3, M4) in view of the state information and the environment information; generating (23) a particular feature vector for each maneuver (M1, M2, M3, M4); on the basis of the particular feature vector, inferring (24) costs for each maneuver (M1, M2, M3, M4) with respect to an optimization problem which comprises one or more trajectory-based cost functionals, by means of a machine learning algorithm trained for this purpose; and, according to the inferred costs, selecting (25) one or more of the maneuvers (M1, M2, M3, M4), preferably together with a specific sequence, for a detailed cost evaluation on the basis of the optimization problem.

This invention relates to the field of information processing technology and discloses a method and system for evaluating software function points based on a large model. The method includes: preprocessing text data from a pre-set enterprise R&D efficiency training library to obtain a preprocessed corpus; initializing the model parameters of a pre-trained model; inputting the labeled dataset from the corpus into the pre-trained model for iterative training to obtain a trained target model; inputting the test dataset corresponding to the function points of the software under test into the target model for calculation to obtain function point size estimation parameters and enterprise production efficiency parameters; and calculating the estimated cost of the software under test based on the function point size estimation parameters, enterprise production efficiency parameters, and a pre-set cost estimation algorithm. Therefore, implementing this invention can unify the process and quantification standards for enterprise software cost estimation, improve the applicability of software cost estimation schemes, and thus improve the efficiency and accuracy of software cost assessment.

The application relates to the technical field of power system cost analysis, in particular to a multi-dimension cost evaluation method and device based on a multi-value coordinated dispatching framework, wherein the method comprises the following steps: determining a safety-economy-low-carbon multi-value coordinated dispatching framework of a power system; under the multi-value coordinated dispatching framework, constructing a unit power demand dispatching cost minimization model based on power energy dispatching demand information and auxiliary service dispatching demand information, and constructing a unit participating dispatching maximum income model based on payment information and environmental premium information; and constructing a unit cost evaluation model to obtain a full-value evaluation result of the power system. Therefore, the problems that in the related art, the cost evaluation cannot comprehensively consider the combination of stable energy supply, orderly resource regulation, clean and environment-friendly low carbon, and the comprehensive feedback and coordination of the power energy value, safety value and green value of various subjects in the power system cannot be realized are solved.