249 results about "Cost analysis" patented technology

The invention relates to an internet big data extraction method and device, equipment and a storage medium, and the method comprises the following steps: carrying out distributed crawler collection on an internet data source, obtaining original network data, and converting the original network data into a structured data matrix; and performing multi-level semantic analysis on the matrix, constructing a semantic feature map, and performing topic segmentation and classification to form a topic domain knowledge tree. Association rules in the knowledge tree are further mined, and an implicit knowledge network is constructed. Performing semantic decomposition and expansion on query conditions based on the network to generate expanded query data, and performing similarity matching with the knowledge network to obtain a candidate data set; and finally, performing multi-factor sorting and extraction on the candidate data, and outputting target data, thereby solving the technical problem that in the second-hand car market, due to wide data sources and fuzzy semantics, an existing system has relatively large deviation when performing price prediction and maintenance cost analysis.

The invention provides a production control method and system based on a digital factory, and the method comprises the steps: collecting the real-time operation data of production equipment in multiple regions of the factory, and carrying out the standardized fusion processing, and obtaining a standardized data flow; according to the standardized data flow, in combination with a preset digital factory knowledge graph, analyzing an association relationship among the production elements to obtain key influence factors; based on the key influence factors in combination with a preset multi-dimensional cost analysis model, optimally allocating production tasks to obtain a production control instruction; and issuing the production control instruction to the production equipment of the corresponding area, monitoring the production parameter change of each area, and dynamically adjusting the production control instruction according to the production parameter change. According to the method, through standardized fusion and knowledge graph analysis of multi-region data, accurate identification of production element association relationships and extraction of key influence factors are realized, the resource utilization efficiency is improved based on optimal allocation of a multi-dimensional cost model, and a dynamic monitoring and adjusting mechanism enhances the response capability to changes.

The invention relates to the technical field of industrial equipment predictive maintenance and asset management, in particular to a machine vision equipment operation and maintenance cost analysis intelligent management method, which comprises the following steps of: acquiring equipment operation state, external environment and historical operation and maintenance work order data through a sensor group and an equipment log interface, and fusing and removing redundancy to form a multi-source data stream; static and dynamic features are extracted by using a pre-trained health state evaluation model and fused by means of an attention mechanism, and a real-time health state index in a 0-1 interval is output; constructing a dynamic cost prediction model, taking health related parameters, spare parts, manpower and depreciation cost as input, and predicting expected operation and maintenance cost of a specific time window in the future; establishing an optimization decision model by taking minimization of the total operation and maintenance cost and maximization of the equipment availability rate as double targets, and generating an optimal maintenance, spare part purchasing and scheduling scheme; and executing the scheme and acquiring actual data, comparing the actual data with a predicted value for feedback, and iteratively optimizing the core model. The operation and maintenance management accuracy and economy are improved, and the method is suitable for intelligent operation and maintenance of the machine vision equipment.

The invention belongs to the technical field of project management and intelligent supervision, and discloses a project cost accounting management method and system for project supervision, and the method comprises the steps: inputting a preprocessing data packet into an edge calculation node, carrying out the dynamic data cleaning through employing a noise filtering matrix algorithm, and outputting a structured data set with a quality label; on the basis of the structured data set with the quality label, scanning a construction part through augmented reality glasses, comparing actual coordinates with building information model design coordinates in real time, and when a deviation accumulated value exceeds an early warning threshold value, generating an acceptance evidence chain which cannot be tampered; and accumulating the incremental cost of the plurality of standardized visa file packages, carrying out time sequence analysis through a long-short term memory prediction model, and outputting a project cost analysis report with a risk level. The problem of loss of acceptance evidence chains in traditional cost accounting is solved, and the strong dependence of a conventional prediction model on data distribution is broken through.

The invention relates to the technical field of hot-line work assessment, and discloses a hot-line work risk assessment method and system based on multi-source data, and the method comprises the steps: collecting equipment data, environment data and geological data, and carrying out the preprocessing; the method comprises the following steps: constructing a knowledge graph structure based on connection of electrified equipment, calculating link cost, analyzing node priority change to carry out dynamic shortest path calculation, optimizing risk propagation of abnormal points, calculating risk change of each grid point, and carrying out anomaly detection. According to the method, the physical and logic relations between the nodes are determined through the knowledge graph, multi-dimensional risk modeling and analysis are facilitated, the method can adapt to field data changes and reflect the newest risk distribution state through real-time monitoring and updating of node priority ranking, negative weight edges are supported through the Bellman-Ford algorithm, and the method has the advantages of being high in reliability and high in reliability. Possible negative influence factors in risk propagation can be effectively processed, the risk diffusion range and intensity of nodes can be accurately described through a Gaussian diffusion model, and the influence of the nodes on surrounding grid points is quantified.

The invention discloses an unmanned aerial vehicle autonomous address selection method based on terrain evaluation and approach cost analysis, and relates to the technical field of unmanned aerial vehicle autonomous address selection. After the unmanned aerial vehicle receives a landing instruction in an unknown environment, the geometric safety of the terrain and the cost problem of the approach path can be comprehensively considered, and the landing point selection strategy of the unmanned aerial vehicle is optimized from the global perspective. Firstly, semantic segmentation is performed on an RGB image acquired by a visual sensor through deep learning to acquire a semantic image, then point cloud data acquired by a laser radar and the semantic image are fused to acquire a three-dimensional semantic point cloud, and a terrain safety area conforming to terrain geometric feature constraints is screened out on the basis of considering semantic tags. And finally, calculating the cost of the linear approach path of each candidate landing point in the terrain safety area through traversal, and screening out the landing point with the optimal comprehensive cost, thereby improving the accuracy and practicability of terrain safety area identification. According to the method, an unreachable or high-risk area is avoided, and the global point selection optimization effect is improved.

Computer implemented methods, systems, and computer program products include program code executing on a processor(s) to: obtain queries (each query including workload(s)); obtain execution statistics for the one or more workloads; normalize one or more queries. Normalizing includes generating cost analytics, identifying similar cost analytics for query blocks across the queries, and applying a cost model to identify at least one query block for result reuse across. The program code distributes the queries to system resources by assigning the at least one query block (in more than one query / workload) to a first resource to execute (as part of a first workload) against database tables and assigning the at least one query block to a second resource to execute (as part of a first workload) against a shared cache of a heterogenous database system.

The invention discloses a construction engineering cost analysis system and method, and particularly relates to the technical field of construction cost behavior monitoring, and the method comprises the following steps: collecting the business information and field process information of an execution stage project, carrying out the field-level matching with a budget detail table, and constructing a data set; performing risk judgment according to the contract plan information and the actual execution information, and judging whether to start a risk identification process; executing multi-dimensional information cross-analysis to identify cost risk symptoms when the conditions are met; calculating dynamically updated first and second risk assessment factors based on the identification result, and inputting the first and second risk assessment factors into a risk assessment model to generate a comprehensive cost risk score; according to the method, accurate matching of the budget information and the execution data is realized, and the real-time sensing capability of the cost data is improved; through a dynamic risk identification and cross analysis mechanism, the early discovery and judgment capability of the cost abnormity is enhanced; and a two-factor evaluation and scoring model is constructed, so that quantitative expression and intelligent early warning of the cost risk are realized.

The invention relates to the technical field of data query, can be applied to business scenes such as financial science and technology and medical health, and discloses a data query statement dynamic generation method and device, equipment and a medium, and the method comprises the steps: receiving query request information, matching business strategies, completing conflict resolution, and generating a target business strategy set; obtaining dynamic context information formed by a database structure, an index, statistical information and a system load; and generating an initial data query statement based on the target business strategy set, the dynamic context information and the query request information, and obtaining an executable data query statement through grammar verification, logic optimization and execution cost analysis. According to the method, service rule analysis, conflict resolution and environment perception are combined, so that the query statement generation process can be adaptively adjusted along with the change of the service rules and the change of the running state of the database, and the accuracy and execution efficiency of query statement generation are improved while the correctness of service logic is kept.

Computer implemented methods, systems, and computer program products include program code executing on a processor(s) to: obtain queries (each query including workload(s)); obtain execution statistics for the one or more workloads; normalize one or more queries. Normalizing includes generating cost analytics, identifying similar cost analytics for query blocks across the queries, and applying a cost model to identify at least one query block for result reuse across. The program code distributes the queries to system resources by assigning the at least one query block (in more than one query / workload) to a first resource to execute (as part of a first workload) against database tables and assigning the at least one query block to a second resource to execute (as part of a first workload) against a shared cache of a heterogenous database system.

The invention discloses a health condition evaluation method and system for new energy equipment, and the main points of the technical scheme are that the method comprises the following steps: multi-source data collection and preprocessing: deploying a sensor array to collect equipment operation data, fault feature data, environment data and operation and maintenance historical data, employing an EMD-SVD algorithm to carry out the denoising of a vibration signal, and carrying out the preprocessing of the data; processing the multi-dimensional data through Z-score standardization; constructing a dynamic weight calculation model; health state grading evaluation; and health trend prediction and active early warning: constructing an LSTM-Attention prediction model, inputting a historical CHI sequence, operation data and environmental parameters, and outputting health state prediction values in future 1-3 months. A complete closed loop is formed from data acquisition, evaluation and prediction to operation and maintenance decision, full-life-cycle health archive management of equipment is supported, and data support is provided for equipment type selection optimization and life cycle cost analysis.

A system and method are provided for controlling item placement for managing warehouse productivity. The system may include one or more warehouse databases, and one or more processors. The processors may be configured to interface with the one or more warehouse databases, extract, transform and load information from the one or more warehouse databases to form an input dataset, perform cost analysis and discrete event simulation to the input dataset to obtain a candidate dataset, and provide a recommendation for an optimal mix of volume flow through different forward pick areas of a warehouse by applying a linear programming solver on the candidate dataset.

The invention relates to the technical field of financial data processing, in particular to a payment and settlement service system based on a big data technology, and the system comprises a data collection module, a user payment behavior recognition module, a payment channel evaluation module, and a payment execution and monitoring module. According to the invention, through deep analysis of transaction data and dynamic user portrait construction, consumption modes and preference trends of users can be captured and analyzed more accurately, and through extraction of periodic purchase behaviors and sudden change preferences, payment experience is highly personalized, customer service quality is greatly improved, payment channel assessment is comprehensive, and user experience is improved. The method includes real-time performance monitoring and cost analysis, guarantees the optimization of the payment process, effectively improves the processing speed and safety, reduces the fraud risk, enhances the transaction safety and transparency through the implementation of full-chain encryption and the real-time tracking of the payment progress, and improves the response speed to potential abnormalities.

The invention provides a comprehensive evaluation method, system and device based on single coke quality and mixed coke use and a readable storage medium, and the method comprises the steps: constructing a multi-layer progressive evaluation system from single coke quality evaluation to mixed coke performance prediction, and then to economical efficiency dynamic optimization; performing quantitative evaluation on the quality of the single coke through the basic evaluation layer to obtain a quality index; predicting a synergistic effect of various coke proportions through the mixing performance layer, and determining a mixing performance index; performing cost analysis on the proportioning scheme by combining an economic evaluation layer with price fluctuation to obtain a cost performance index; and a plurality of matching schemes are generated through the dynamic optimization layer, and an optimal solution meeting balance of quality, performance and cost is output.

The invention provides a mine comprehensive management and control technology direct production cost analysis system, and the system comprises a direct production cost analysis module which is used for analyzing all target cost class data of a to-be-analyzed mine through a production cost decomposition model which carries out the training of cost class data, so as to obtain the production cost data of the to-be-analyzed mine; the single equipment cost analysis module is used for analyzing all target equipment cost class data of the to-be-analyzed mine through a single equipment cost decomposition model trained by the equipment cost class data so as to obtain equipment cost data of each single equipment; and the application display module is used for displaying the production cost data and the equipment cost data. Therefore, the direct production cost analysis system is developed on the basis of the direct production cost decomposition model and the single equipment decomposition model, so that the control function of the mine production cost from overall analysis to single equipment analysis dimension is realized, the real-time dynamic control of the production cost is realized, and the production cost is greatly reduced.

The invention relates to the technical field of cost analysis, in particular to a visual municipal engineering cost analysis system which comprises an interval wireframe construction module, a construction node positioning module, a budget map grid generation module, a node budget linkage module and a map structure display module. According to the method, cost values of construction units are divided according to interval step lengths, sorting and median difference evaluation are introduced, node positioning is performed in combination with a coordinate mapping mode, and a binding relationship between data and space is formed, so that budget information is subjected to partition homing and ordered stacking in a two-dimensional map; the construction unit construction cost distribution, the budget weight and the graph structure are dynamically fused and displayed in a visual interface, the construction unit construction cost and budget change can be quickly and synchronously adjusted by means of a linkage mechanism of a construction interval and graph grid coordinates, and position updating and graph block rearrangement after node addition and deletion are supported. And the data classification statistical efficiency, the node budget positioning precision, the budget adjustment response speed and the integration degree of map information display are improved.

In a method for data recovery in a continuous data protection system, delta values representing an exclusive disjunction between successive values of data block contents of a content fragment of a dataset at a time t(n) and a time t(n−1) for n=1 to i, where i is selected according to a predetermined data protection profile, are generated. The delta values can be used to recover a dataset to a value at the selected point in time in association with a snapshot that is selected as a starting point for recovery based on a cost analysis associated with a volume of disk activity to restore.

The invention discloses a park electric energy intelligent management regulation and control method based on the Internet of Things, and belongs to the technical field of community power grid building platforms, and the park electric energy management regulation and control through a management regulation and control platform comprises the steps of firstly installing an intelligent electric meter for data acquisition and monitoring system deployment, and then training a load prediction model by using historical load data, and finally, according to the trained load prediction model, predicting time-sharing electric power of the proprietors in the future. And meanwhile, according to future weather forecast data, a reference electricity price model is established in a linear regression mode, so that the future time-sharing reference electricity price is predicted. After various basic data are prepared, a park power supply and demand model is constructed in a linear programming mode, the total power consumption cost is minimized, in subsequent power supply management, a manual intervention step is added, the power consumption ratio, cost analysis and energy storage state of each owner are displayed through a visual component, a threshold value is set, and when the detected deviation exceeds the threshold value, the power supply management is completed. And prompting an administrator for intervention.

The invention discloses a power transmission and transformation project cost analysis model construction method based on quantitative indexes, and belongs to the technical field of electric power project cost, and the method comprises the steps: S1, carrying out the semantic recognition of first historical power transmission and transformation project data based on natural language processing, and constructing a final feature library; s2, performing quantitative index and quantitative index correlation extraction on the final feature library based on a convolutional neural network to establish a first initial cost analysis model; s3, constructing an adaptive simplification model at least comprising a weight calculation rule and a similar engineering screening rule based on a discriminant clustering algorithm and an AHP method; and S4, updating the first initial cost analysis model based on the self-adaptive simplified model to obtain a project cost analysis model. The technical problem that it is difficult to improve the discrimination efficiency while improving the discrimination accuracy of the same kind of engineering is solved, the model complexity is reduced, and the discrimination accuracy and efficiency of the same kind of engineering are remarkably improved.

The invention provides an enterprise operation cost analysis method and device based on privacy calculation, equipment and a medium, and belongs to the technical field of data processing.The method comprises the steps that an enterprise data source is determined, and a data collection interface is set to collect, pre-process and encrypt service data; constructing a privacy computing platform, wherein each data source and the privacy computing platform construct a unified enterprise operation cost analysis basic model through a federal learning mode; carrying out encryption calculation among the data sources in a multi-party security calculation mode, and uploading an encryption calculation result to the privacy calculation platform; and the unified enterprise operation cost analysis basic model is optimized by using the encrypted calculation result on the privacy calculation platform, then the optimized unified enterprise operation cost analysis basic model is used for enterprise operation privacy calculation, and different viewing permissions are set for the enterprise operation privacy calculation result. According to the method, the enterprise data privacy is fully protected, and the accuracy and efficiency of operating cost analysis are improved.

The invention discloses a power grid frequency coordinated regulation and control method and device based on coordination of three defense lines, and the method comprises the steps: carrying out the control cost analysis, constructing an interconnected power grid active frequency response model based on the control cost analysis, and building an active frequency response control strategy of coordination of the three defense lines on this basis, wherein the three defensive lines comprise prevention control, emergency control and correction control, and finally, a target function is constructed by taking the minimum total cost of the three stages of prevention control, emergency control and correction control as a target, so that the optimization space for coordinated operation of the three defensive lines for power system frequency stability is improved, and the control target of safety and economy coordination is further realized. The relationship between the control cost and the system frequency safety is coordinated, and the purpose of safe and economic cooperative control of the alternating-current and direct-current hybrid system for the frequency stability problem is achieved.

The invention discloses an electric power engineering cost visualization method based on big data processing, and relates to the technical field of electric power engineering, and the method comprises the steps: obtaining electric power engineering multi-source data, and loading a pre-constructed electric power engineering three-dimensional model as a visualization carrier; based on the electric power engineering multi-source data, key entities and cost association relationships are extracted according to project types to construct a cost knowledge graph; according to the cost knowledge graph and the industry specification database, generating a cost analysis result through graph association mining and specification verification; through a hierarchical dynamic mapping algorithm, performing semantic structuring processing on the cost analysis result according to a plurality of hierarchies of a project population, sub-project and equipment parts, and binding with spatial positions of components of corresponding hierarchies in the three-dimensional model of the electric power project to generate a visual mapping result; and in response to the multi-modal interaction instruction, positioning a target component in the three-dimensional model of the electric power engineering based on the sight line of the user, and displaying a cost analysis result constructed with the target component.

The invention discloses a project cost analysis method, electronic equipment, a readable storage medium and a program product, and relates to the technical field of project management, and the project cost analysis method comprises the steps: obtaining various types of original data of a target project in a target system to which the target project belongs; each type of original data comprises project type data, system type data and product type data; generating each associated data combination according to the data with the association relationship between every two data in each type of original data; determining the similarity between two pieces of data contained in each associated data combination, and taking each associated data combination with the similarity greater than a preset similarity threshold as each target combination; performing association processing on data contained in all the target combinations to obtain an associated data set of the target project; and analyzing the cost of the target project based on the associated data set. The analysis efficiency and the analysis accuracy of the project cost can be improved.

The invention relates to the field of engineering construction, in particular to a construction cost analysis system and method based on big data. The method comprises the following steps: acquiring multi-modal construction data in a system, sequentially performing data preprocessing and standardization on the multi-modal construction data, aligning texts and numerical values in the initial multi-modal construction data, constructing a knowledge graph by using aligned text numerical value data and image spatio-temporal data, and connecting an LSTM-GRU hybrid network with an HMM hidden Markov model. The method comprises the following steps: establishing a construction cost prediction model, adding a space-time attention mechanism in the model, inputting feature multi-modal construction data into the model for prediction, iterating model training through a PPO algorithm, and carrying out unified scheduling management on materials and manpower in a construction project based on a minimum cost path and a risk plan library. Key space-time regions can be dynamically focused, so that the spatial resolution of a prediction result is improved to a section level, and a basis is provided for accurate scheduling.

The invention relates to a project cost data analysis method and system. The method comprises the steps of obtaining a plurality of historical project cost data samples; training the plurality of initial network models according to engineering materials, construction processes, engineering costs and cost analysis information of the historical engineering cost data samples of the plurality of engineering categories to obtain cost data analysis models corresponding to the various engineering categories; according to the engineering geological information and the building height of the target engineering cost data, performing clustering analysis on the target engineering cost data to obtain a target engineering category; determining a cost data analysis model corresponding to the target project category as a target model; and inputting the engineering material, the construction process and the engineering cost of the target engineering cost data into the target model, and obtaining a target engineering cost analysis result output by the target model, so that the efficiency and the accuracy of obtaining the engineering cost data analysis can be improved.

The invention relates to the technical field of micro-grid system energy management, in particular to a micro-grid planning method and system for multi-micro-grid coupling. The method comprises the following steps: establishing a capability construction dimension diagram for each micro-grid, setting a quantitative standard to quantify the dimension diagram into a capability construction index, evaluating the existing capability of each micro-grid according to the capability construction index, calculating the electric energy transmission loss in the coupling process, and determining the capacity of each micro-grid according to the benefit improvement and loss cost brought by the coupling. Benefit-cost analysis is carried out, an intelligent scheduling strategy is generated, a resource constraint function and a target constraint function are established, a plurality of coupling schemes are generated for each micro-grid according to a multi-micro-grid coordination algorithm, and benefit overflow values of the schemes are compared through the multi-micro-grid coordination algorithm. According to the micro-grid planning method and system for multi-micro-grid coupling provided by the invention, coordinated operation and resource optimization configuration among multiple micro-grids are realized, the energy utilization efficiency of the whole system is improved, the operation cost is reduced, and the power supply reliability is enhanced.

The invention discloses a multi-dimensional Internet data center cost analysis system and analysis method, and the method comprises the steps: building a data interface platform, carrying out the butt joint with a data source, and automatically collecting multi-dimensional cost data; establishing a multi-level data aggregation model based on a time sequence, and performing data integration according to a plurality of analysis dimensions; a hierarchical calculation engine is adopted, derivative indexes are obtained through further calculation according to the basic indexes, cost allocation results and related data are obtained through calculation of the derivative indexes, and the results are visually displayed; according to the method, automatic acquisition, multi-dimensional integration, precise calculation and visual display of the IDC cost are realized based on an intelligent fusion technology of multi-source heterogeneous data and multiple dimensions of business rules, and powerful decision support is provided for IDC operation management.

The invention belongs to the technical field of data analysis, and discloses a petroleum cost analysis method and system based on data analysis. The method comprises the following steps: collecting real-time full-life-cycle data of a petroleum project, and extracting real-time multi-dimensional cost data in the real-time full-life-cycle data; performing petroleum cost analysis by using a petroleum cost analysis model according to the real-time multi-dimensional cost data to obtain a real-time petroleum cost analysis result; and generating a project optimization strategy by using the project optimization model according to a real-time petroleum cost analysis result to obtain a real-time project optimization strategy. The method solves the problems of data acquisition lagging and fragmentation, lack of real-time performance and integrity, single cost dimension, insufficient analysis depth, extensive analysis method, low prediction precision, lack of dynamic optimization decision support and difficulty in coping with uncertainty in the prior art.

The invention discloses a cold-chain logistics electric vehicle path optimization method based on model decomposition, and relates to the technical field of electric vehicle path planning, and the method comprises the steps: obtaining path planning reference data, constructing a cost analysis model, building a partial nonlinear charging model, and selecting a model decomposition strategy. A solution mode is dynamically adjusted according to the number of customers, a random allocation algorithm is adopted in a small scale to be combined with the first model, a clustering-time window sorting algorithm is adopted in a large scale to be combined with the second model, and a CPLEX solver is called to generate a high-quality distribution scheme. According to the method, the problem complexity can be remarkably reduced, the solving time is shortened, the flexibility of small-scale and large-scale problems is considered, meanwhile, the fresh product distribution timeliness is enhanced, and the distribution cost is optimized.

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.