44 results about "Cost–benefit analysis" patented technology

The invention relates to the technical field of agricultural data dynamic perception, in particular to an agricultural data dynamic perception scheduling method based on the Internet of Things, and the method is realized based on an Internet of Things sensor, an edge computing platform and an edge server. Comprising the following steps: deploying Internet of Things sensors including a meteorological station, a soil humidity monitor and an unmanned aerial vehicle inspection system, and deploying a real-time data processing module on an edge server through an edge computing platform. According to the method, a dynamic cost-benefit analysis model is constructed, various factors and dynamic changes in agricultural production are comprehensively considered, a multi-objective optimization algorithm and a dynamic planning technology are applied, optimization of resource allocation and maximization of long-term benefits are achieved, in addition, uncertainty factors are processed by introducing a fuzzy mathematical method, and the method is suitable for large-scale popularization and application. The method improves the robustness and reliability of analysis, and solves the problems of lack of dynamics, incomplete consideration factors and limited optimization means in a traditional scheme.

The invention relates to the technical field of intelligent data management, in particular to an industrial park project management control method and system based on big data, and the method comprises the following steps: based on industrial park project data, controlling task progress, resource consumption and budget expenditure, screening progress delay and resource abnormity tasks, extracting a resource allocation path and task priority, and performing task scheduling; resource conflicts are identified, budget imbalance is identified, quality and cost benefit analysis is output, external fluctuation and policy changes are captured, and risk triggering nodes are identified. According to the invention, through comprehensive control and monitoring of industrial park project management data, tasks with progress delay and abnormal resource consumption can be efficiently screened, efficient management of project nodes is ensured, through analysis of budget configuration and task complexity proportion, a budget imbalance problem is accurately identified, risks are identified in advance, predictability and response speed of project management are improved, and project management efficiency is improved. Delay and resource waste are reduced, decision support capability and data collaboration efficiency are enhanced, and smooth execution of a project is ensured.

The invention discloses an informatization management method for building construction, and relates to the technical field of building informatization management, and the method comprises the steps: carrying out the real-time data collection through employing various sensors installed at a construction site, and a data collection module, extracting the collection data in the same time period from a time series data sequence, and carrying out the data collection through employing a data informatization management module, the method comprises the following steps: respectively calculating a construction efficiency evaluation value XLP, a cost-benefit analysis value CXF and a quality risk prediction value ZL, evaluating the quality risk level of a construction project according to the quality risk prediction value ZL, and comparing the construction efficiency evaluation value XLP with a construction efficiency evaluation value XLPprev of a previous stage and comparing the cost-benefit analysis value CXF with a cost-benefit analysis value CXFprev of the previous stage to obtain the quality risk level of the construction project. According to the method, through optimization and innovation means such as data integration and sharing, scientific evaluation and accurate decision, dynamic adjustment and feedback mechanism and the like, the construction efficiency is improved, the cost risk is reduced, the quality level is improved, and the decision-making ability is enhanced.

A system and method for automated cybersecurity defensive strategy analysis that predicts the evolution of new cybersecurity attack strategies and makes recommendations for cybersecurity improvements to networked systems based on a cost / benefit analysis. The system and method use machine learning algorithms to run simulated attack and defense strategies against a model of the networked system created using a directed graph. Recommendations are generated based on an analysis of the simulation results against a variety of cost / benefit indicators.

A system and method for automated cybersecurity defensive strategy analysis that predicts the evolution of new cybersecurity attack strategies and makes recommendations for cybersecurity improvements to networked systems based on a cost / benefit analysis. The system and method use machine learning algorithms to run simulated attack and defense strategies against a model of the networked system created using a directed graph. Recommendations are generated based on an analysis of the simulation results against a variety of cost / benefit indicators.

The invention belongs to the technical field of cold and heat source configuration methods, and particularly relates to a cold and heat source configuration optimization method and system based on a full life cycle, and the method comprises the steps: S1, building use characteristic analysis; s2, designing a staged unit configuration scheme; s3, optimizing an intelligent control strategy; s4, carrying out full-life-cycle cost-benefit analysis; s5, optimal scheme decision making and dynamic adjustment; according to the method, a dynamic prediction model of a time sequence analysis and Transform-TCN hybrid architecture is adopted, historical load data can be deeply mined through time sequence analysis, and time characteristics and periodic rules in the data are captured; the long sequence modeling capability of the Transform and the local feature extraction capability of the TCN are combined by the Transform-TCN hybrid architecture, so that the long and short term dependency relationship in the load data can be better processed, and the prediction accuracy is improved.

The invention discloses a calculation method for waste aluminum optimal proportion and raw material cost in 6-series aluminum alloy round ingot smelting, which comprises the following steps of: firstly, determining suitability and maximum additive amount of waste aluminum: determining component calculation values of all elements according to a preset rule by comparing target alloy component requirements with actual components of the waste aluminum; and calculating the additive amount limited by each element, taking the minimum value of the additive amount as the theoretical maximum additive amount, and judging whether the economic threshold value is reached or not. And for the waste aluminum suitable for addition, cost-benefit analysis is carried out subsequently: the reference cost of not using the waste aluminum and the scheme cost of using the maximum addition amount of the waste aluminum are calculated respectively, and the economic feasibility of purchase and use is evaluated by comparing the reference cost and the scheme cost. According to the method, technical feasibility and economic analysis are combined, a quantitative decision support method is formed, whole-process optimization from casting matching to purchase decision is achieved, and the resource utilization rate is remarkably increased and the production cost is reduced while the stable quality of aluminum alloy products is guaranteed.

The invention discloses a production operation and inspection cost pricing system improvement method based on cost benefit analysis, and relates to the technical field of cost pricing, and the method comprises the following steps: collecting cost data in a production operation and inspection process, and dividing the collected cost data into direct cost and indirect cost; based on a cost-benefit analysis method, performing systematic evaluation on the collected cost data, calculating economic benefit indexes of various costs, and comprehensively comparing the costs and benefits to obtain a cost-benefit coefficient; according to the cost-benefit coefficient and the economic benefit index, a production operation and inspection cost pricing model is constructed based on an operation cost method; a dynamic adjustment mechanism is established, and relevant parameters and indexes in the cost pricing system are updated and adjusted regularly. According to the invention, by establishing a dynamic adjustment mechanism, related parameters and indexes in the cost pricing system are updated and adjusted regularly, and the accuracy and practicability of the cost pricing model are ensured.

The invention discloses a watershed ditch and pond-road low-cost ecological sand control method based on hydrological connectivity, which belongs to the field of ecological environment protection and mainly comprises the steps of data acquisition, DEM data correction, confluence network construction, hydrological structure connectivity identification, SWAT model construction, key source area identification, scene analysis and cost benefit analysis. Under the influence of a ditch pond-road system, the key source area identification technology based on hydrological structure connectivity and the drainage basin key source area ditch pond road low-cost water regulation and soil conservation method achieve the dual purposes of reducing the water and soil regulation and control cost and continuously improving the ecological benefit by identifying the key source area.

The invention discloses a regional heat supply centralized control system based on economics, and the system comprises a nonlinear cost sensing heat supply regulation and control module which is responsible for receiving real-time temperature data from a heat supply system and temperature preference set by a user, calculating a temperature threshold value based on a foreground theory, and prompting the increase of heat supply cost in real time. And the contrast between the incremental cost and the energy saving is displayed through a visual chart. According to the method, the behavioral economics theory is introduced, a heat supply strategy optimization model of the system is formed based on cost-benefit analysis and a marginal cost theory, a data model of user decision preference is constructed through sensor and user feedback data, irrational behavior characteristics are mined, and the behavioral economics principle is embedded into a system algorithm. Dynamic optimization of heating regulation and control and user incentive strategies is achieved, meanwhile, data visualization and immediate feedback design are strengthened, the energy-saving effect and cost effectiveness are visual and visible, and unification of heating economical efficiency, energy efficiency and user welfare is achieved.

The invention discloses a multi-dimensional evaluation method of a blast furnace process extreme energy efficiency technology, and relates to the field of steel production energy efficiency evaluation. Aiming at six extreme energy efficiency technologies of a blast furnace process, a'technical unit energy-saving cost (CCEa)-net present value (NPV)-internal return rate (IRR) 'ternary index system is constructed, an energy-saving supply curve and a cost-benefit analysis method are combined, and comprehensive evaluation is realized through four steps: calculating the energy-saving and emission-reducing potential when the blast furnace uses anthracite, and introducing exclusive emission factor correction; calculating the unit energy-saving cost considering the multi-pollutant synergistic benefit, and combining the exclusive reachable rate of the technology; the full-life-cycle cost effectiveness is analyzed from the perspective of enterprises, and technology maturity correction is introduced; and carrying out dynamic weighted sorting based on a TOPSIS method, and outputting technical priorities. The method breaks through the limitation of single-dimensional evaluation, realizes the collaborative evaluation of economic and environmental benefits, and provides a decision basis for the low-carbon transformation of the blast furnace.

This invention discloses a cost-benefit analysis method for the joint operation of distribution network edge resources based on multi-energy complementarity. The cost analysis consists of three parts: initial investment cost, operating cost, and wind power cost. Based on the existing centralized gas heating method, the converted electricity price and subsidy fees are calculated. Finally, by comparing with the existing heating subsidy policy, the benefits of the gas-curtailed wind complementary method are analyzed. The advantages of this invention are: considering factors such as environment, temperature regulation, energy saving, and safety, the gas-curtailed wind complementary heating method has advantages such as low initial investment cost, stable operation, low maintenance, safety and no pollution, and good economic efficiency.

The invention discloses an enterprise multi-level relation rapid retrieval method and system based on a knowledge graph, and relates to the technical field of enterprise management, and the method comprises the steps: collecting internal and external multi-source heterogeneous data of an enterprise, controlling the collection time, and carrying out the legality verification of the collected data; receiving the verified data, constructing an enterprise knowledge graph, and optimizing a knowledge graph association rule based on monthly newly added data; based on the knowledge graph, receiving a retrieval request through a query interface, and returning a retrieval result; and applying the retrieval result to cost-benefit analysis of association between enterprises, including association cost accounting, association benefit evaluation, cost-benefit association mining, intelligent prediction or abnormal early warning traceability. The method has the advantages that the accuracy and efficiency of enterprise relationship risk identification, investment decision support and strategic planning are effectively improved by constructing the multi-dimensional associated knowledge graph between the enterprises, and comprehensive data support and intelligent decision support are provided for the enterprises to manage complex commercial relationships.

The invention provides a carbon compensation method based on cross-regional power trade transfer, and relates to the technical field of energy environments. According to the method, through constructing a power transaction carbon emission reduction responsibility accounting model, an emission reduction effort-based carbon emission reduction responsibility allocation model and a carbon compensation cost benefit analysis model, accurate allocation and fair compensation of carbon emission reduction responsibility in cross-regional power transaction are realized. Through accurate responsibility accounting, responsibility allocation considering economic and technical contributions and scientific economical efficiency verification, the defects that in the prior art, responsibility allocation is one-sided, technical investment and economic benefit allocation are difficult to reflect, and economical efficiency verification is lacked are overcome; and a scientific, fair, economical and feasible solution is provided for carbon emission reduction responsibility distribution and compensation in cross-regional power transaction.

The invention discloses a typical resource multi-scale cost-benefit analysis method and system, and relates to the technical field of resource analysis, and the method comprises the following steps: firstly analyzing the correlation characteristics of typical resources, and obtaining basic data; based on the basic data, performing energy complementarity analysis, and making a demand response strategy; and constructing the multi-energy complementary system according to the demand response strategy. The invention provides a comprehensive and systematic way for evaluating typical resources, and can deeply research the internal correlation characteristics of various resources and the influence of the internal correlation characteristics on the cost and benefits, thereby realizing the optimal configuration and use of the resources. Through the analysis method, the energy utilization efficiency can be improved, the energy cost can be reduced, enterprises and policy formulators can be helped to formulate energy policies and management strategies more scientifically, and remarkable social benefits and economic benefits are achieved.

The invention discloses a method for improving flexible power supply capacity through synchronous configuration of a wind-solar storage network, and belongs to the technical field of power system automation and new energy grid connection. According to the method, for a grid-connected micro-grid containing a battery energy storage system, solar energy and wind energy, a dual-target optimization model integrating voltage deviation and power loss is established, and the locating and sizing of a distributed power supply and energy storage and a BESS charging and discharging plan are optimized in a collaborative mode. Based on a node system, in combination with four-season load and wind-solar output data, an optimal access position is analyzed and determined by adopting loss sensitive factors, uncertainty is processed by utilizing a point estimation method, and loss is further reduced through power distribution network reconstruction. And meanwhile, data preprocessing and cost-benefit analysis are introduced, so that the model precision and economic feasibility are improved. The method can significantly reduce the network loss, improve the voltage quality, improve the system operation efficiency and the power supply flexibility, and is suitable for the optimal configuration of the power distribution network in a high-proportion renewable energy access scene.

Disclosed is a configuration for managing the organization of data tables in cloud-based storage. The configuration receives metrics for data processing operations on the data table. Metrics include at least one of a size of the data table, a size of each file in the data table, and metadata describing the data table. The configuration automatically executes a cost-benefit analysis based on the one or more metrics for each candidate maintenance operation in a plurality of candidate maintenance operations. The configuration automatically selects a maintenance operation from the candidate maintenance operations to automate based on the cost-benefit analysis of the one or more candidate maintenance operations. The selected maintenance operation is automated and scheduled on the data table.

The application discloses a highway expansion mode decision method based on a whole life cycle cost benefit, and comprises the following steps: S1, highway expansion period construction cost is estimated; S2, highway expansion period construction carbon emission cost is estimated; S3, highway expansion period operation benefit loss is estimated; S4, highway operation period operation benefit is estimated; S5, highway expansion operation period operation cost is estimated; S6, highway expansion period and operation period vehicle operation carbon emission cost are estimated; S7, based on whole life cycle cost benefit analysis, the expansion scheme is decided.The application considers the construction and operation period carbon emission cost and the expansion period operation benefit loss, so that the whole life cycle cost benefit system of the highway expansion project is more perfect.Facing different expansion modes, the method can be used to complete the total cost benefit analysis of the construction period and the operation period, and the generality of the decision method is improved.

A power distribution network reliability cost-benefit analysis method based on life cycle cost is characterized in that a reliability cost improvement model is constructed with optimal configuration of distributed resources of a power distribution network as a target, and the reliability cost improvement model is a distributed resource reliability cost-benefit oriented double-layer optimization configuration model. The reliability of the distributed resources is accurately predicted and evaluated, so that the cost and income of investment in each stage of planning, construction, operation, decommissioning and the like are systematically considered, and unnecessary cost waste is reduced. The method can achieve the balance of two time scales through the iterative coupling of the planning layer and the operation layer, obtains the final global optimal solution, effectively improves the reliability cost-benefit analysis effect, can obtain the reliability investment comprehensive benefit through employing a proper method according to different power distribution network scales, and improves the reliability cost-benefit analysis efficiency. And the application range of the design is effectively expanded.

The invention discloses a PCB fault detection and repair method based on Bayesian inference. The method comprises the following steps: S1, generating a multi-modal data set; s2, carrying out preprocessing on the multi-modal data set; s3, calculating the posterior probability of the PCB fault by using a Bayesian inference method in combination with the initial prior probability, and generating a preliminary fault diagnosis result; s4, performing time sequence analysis through a Shenchang differential equation; s5, performing approximate inference on posterior distribution in the Bayesian model by adopting a method based on the combination of spread variation inference and normalized flow, and sampling in a high-dimensional space through an adaptive Markov chain Monte Carlo method to generate a final fault diagnosis result; s6, generating an optimal PCB repair scheme by using the intelligent decision tree model in combination with repair cost-benefit analysis; and S7, displaying a fault detection result and a repair suggestion through an interactive user interface. According to the method, the Bayesian inference and the Shenchang differential equation are combined, and efficient and accurate PCB fault detection and optimization repair are achieved.

The invention discloses a fire risk analysis method and system for a ship carrying new energy automobile. The method comprises the steps of assuming a new energy automobile loading condition and a fire scene, determining a life and property loss assumption, establishing a risk matrix, and proposing a fault failure mode hazard source identification guide word. Dividing loading, transportation and unloading nodes and operation behaviors according to a ship transportation vehicle flow, and constructing an event tree-fault tree model; the event tree starts from the fire of the new energy automobile at the roll-on-roll-off place, and layer-by-layer analysis is performed according to the type of the place, early detection and the like; the fault tree and the event tree are subjected to corresponding hierarchical association and subdivision; the accident probability is determined through an initial event probability calculation module and a hierarchical probability quantification system, the result is quantified through property loss grading, and a risk value is calculated; setting risk balance, determining risk control measures, and recommending an optimal risk control scheme for the customer through cost-benefit analysis. The problem that risk control input and output are difficult to balance for a long time in the industry is solved.

An embodiment analyzes, to determine a value of a chemical compound, a first sensor data to determine a density of the chemical compound, where the chemical compound is emitted from a candidate underwater source in a water body where an operation of a floating farm operation is conducted. The embodiment performs a cost-benefit analysis using the value of the chemical compound and a cost of using the chemical compound in the operation of the floating farm. The embodiment causes, in response to the cost-benefit analysis justification for an upwelling movement, the upwelling movement of an upwelling apparatus to a submerged location in the water body. The embodiment causes, in response to the cost-benefit analysis justification for a farm relocation, the farm relocation of the floating farm to a surface location in the water body.

The invention discloses a comprehensive cost recovery model in a power generation subject multi-product market, a solving method, a solving system, a solving device and a medium, and belongs to the technical field of power market operation and optimization. A lower-layer model objective function is constructed, lower-layer model constraint conditions are established based on the lower-layer model objective function, an upper-layer model objective function is constructed, and market indexes, compensation indexes and cost are calculated based on the upper-layer model objective function; converting the constructed lower-layer model through a duality theory, carrying out unified solution with the upper-layer model, transmitting data to the upper-layer model, and calling a solver to calculate the cost recovery condition of the power generation enterprise. According to the invention, a double-layer framework of market clearing simulation and cost benefit analysis is constructed, a multi-market coupling transaction mechanism is represented, and the cost recovery efficiency of the power generation enterprise is improved. A double-layer problem is converted into computable single-layer planning, and complete analysis from market behavior simulation to cost recovery state quantification is formed.

The invention provides an after-sales information management method and system for chip products, and the method comprises the steps: carrying out the text processing of various types of unstructured data in the after-sales information of the chip products, and obtaining structured after-sales basic data; carrying out mining analysis on the after-sales basic data based on an association rule mining algorithm, mining association relationships between different fault phenomena and chip parameters, and obtaining fault association rule data; performing fault cause inference on the fault association rule data by using a Bayesian network algorithm to obtain a fault cause inference result; and aiming at the fault reason inference result, combining historical maintenance cost data, adopting a cost-benefit analysis algorithm, evaluating costs and expected effects of different maintenance schemes, and determining an optimal maintenance strategy as a management result of the after-sales information of the chip product by calculating a cost-benefit ratio. According to the method, a reasonable maintenance scheme is made, so that resource waste is avoided, and enterprise benefit maximization is realized.

The invention provides a high throughput-oriented accurate user traceability attribution method and system, and belongs to the technical field of computer networks, and the method comprises the steps: for each breakpoint position in a track breakpoint set, according to the behavior characteristics and time distribution modes of front and back contacts, calculating missing intermediate contact information through a probabilistic reasoning mechanism, obtaining a complemented user behavior track sequence; according to an attribution weight distribution result, calculating channel optimization suggestion parameters by adopting a cost-benefit analysis algorithm to obtain a quantitative guidance scheme of marketing resource configuration; and continuously processing newly generated user behavior data by adopting a real-time monitoring mechanism through quantizing configuration parameters in a guidance scheme, and triggering a model parameter updating process if detecting that an attribution mode is remarkably changed, so as to obtain a dynamically adjusted marketing effect evaluation system. Through the technical scheme, cross-platform marketing effect attribution can be realized, and the problems of multi-channel data isomerism, user behavior track breakage and difficulty in contact contribution degree quantification are solved.

The present invention relates to a virtual power plant capacity optimization configuration method of multi-agent game, which is characterized by comprising the following steps: step one, multi-investor virtual power plant architecture and its adjustment capability analysis; step two, virtual power plant aggregation model and cost-benefit analysis index composition; step three, multi-investor virtual power plant capacity configuration model; step four, cooperative profit distribution correction model based on improved Shapley value method; the cooperative profit distribution correction model based on improved Shapley value method improves the robustness of virtual power plant capacity configuration model. Beneficial effects: The present invention can successfully cope with various game modes of distributed power investors, effectively improve individual investors' benefits, maximize investor group benefits, stabilize the optimal cooperation model of multiple investors, reduce the risks caused by renewable energy generation and electricity price uncertainty, and improve investment risk resistance.

The invention belongs to the field of safety construction based on electric power construction engineering, and particularly relates to a safety construction management system and method based on electric power construction engineering, and the system comprises a construction site real-time monitoring camera and a sensor network. The intelligent decision-making layer is divided into a risk assessment module, a construction scheme optimization module and an emergency response module; the construction execution layer comprises personnel scheduling, equipment management, material transportation and on-site construction; the data collaboration center comprises a deep learning model, a fault early warning mechanism and a cost benefit analysis module; the deep learning model can process multi-source data, input variables comprise construction progress, safety risk level, weather forecast and cost budget, and output instructions are construction scheme adjustment suggestions and resource allocation optimization schemes. According to the data-driven decision-making mechanism, the system can dynamically adjust the construction scheme according to real-time data, and the construction efficiency and safety are improved.

The invention discloses a project full-life-cycle investment evaluation method and system based on multi-dimensional cost-benefit analysis, and relates to the technical field of planning project benefit evaluation.According to the project full-life-cycle investment evaluation method and system based on multi-dimensional cost-benefit analysis, multi-dimensional benefit indexes are obtained, comprehensive benefit analysis is carried out, project profit analysis is carried out in combination with operation and maintenance cost, discount rate and project construction cost, and the project benefit evaluation efficiency is improved. Dynamic integration of multi-dimensional benefits and cost after project implementation is realized, and implementation effects of the project in a full life cycle can be truly reflected after external interference factors are eliminated; meanwhile, a traditional static financial evaluation framework is broken through, a dynamic multi-dimensional evaluation system with discount revenue as the core is established, the influence of multi-dimensional benefit indexes such as economic benefits, operation benefits and strategic benefits on project values is considered, the adaptability to different industry projects and scenes is guaranteed, and the method is suitable for popularization and application. And the comprehensive value of the project in the whole life cycle can be accurately evaluated.

The invention discloses an organic waste treatment evaluation method based on multi-subject environmental economic cost benefits. The method comprises the following steps: collecting economic data and environmental influence data related to an organic waste treatment and utilization industrialization mode; a cost-benefit analysis method is applied to quantify economic data and comprehensively evaluate economic feasibility; a life cycle evaluation method is used to quantify environmental influence data, check carbon footprint of each link of the organic waste treatment and utilization industry mode, and evaluate environmental influence of each system; bringing into an environmental influence monetization method, and calculating the total environmental income; environmental and economic double factors are considered, a whole-process multi-subject environmental economic cost income comprehensive evaluation model is constructed, and economic and environmental comprehensive benefits of all subjects are evaluated. By adopting the method, comprehensive evaluation is carried out on organic waste treatment by quantifying economic benefits, environmental influences and cost benefits of all main bodies, and a scientific basis is provided for organic waste treatment and utilization subsidy policy decision-making.

The invention provides an employee salary management system based on cloud computing, and the system comprises a cloud collection module which is responsible for collecting employee work, personal information and market salary data; the self-adaptive salary calculation module calculates salary according to the working data and the welfare system based on a rule engine, and checks and encrypts the salary; the employee demission prediction module predicts the demission probability and time by combining work, salary, personal information and market data, and generates an early warning signal and a demission reason; and the decision module calculates a risk rating according to the early warning signal and the demission reason, formulates an intervention strategy or a management scheme, and executes the intervention strategy or the management scheme. Through cloud computing, machine learning, a dynamic rule engine and an automatic decision-making module, a data-driven closed-loop management system is constructed, real-time data convergence, salary strategy second-level updating, remission risk modeling and cost-benefit analysis are realized, and the accuracy, automation and response speed of salary management are improved.