9 results about "Cost benefit" patented technology

The invention discloses a bridge maintenance dynamic decision-making method and system based on multiple dimensions and maintenance standards, and belongs to the technical field of bridge intelligent maintenance, and the method comprises the steps: collecting static basic data and dynamic basic data of a to-be-maintained bridge, and evaluating and determining key parts / components, key diseases, four-stage maintenance standards and three-dimensional indexes; a maintenance scheme library formed by different maintenance schemes is determined, and a to-be-maintained bridge and a maintenance project demand analysis library of the maintenance project amount are screened and determined; analyzing and generating a cost benefit model; and according to the cost-benefit model, calculating the maintenance cost required by the to-be-maintained bridge corresponding to different maintenance standards in the maintenance project demand analysis library and the maintenance benefit generated by maintenance, determining a maintenance project plan library and making a maintenance plan. The bridge maintenance dynamic decision-making method and system disclosed by the invention are helpful to grasp the development trend of bridge technical conditions, standardize maintenance decision-making behaviors, improve the scientific decision-making level and effectively carry out preventive maintenance.

The invention discloses a cost allocation system and method based on a multi-dimensional dynamic allocation rule and related products. The system comprises a data layer, a rule layer and an application layer, the data layer is used for acquiring original data and carrying out data processing on the original data to obtain a standardized cost allocation data set; the rule layer is used for acquiring a standardized cost allocation data set and a service configuration instruction to obtain an executable allocation rule set; wherein the service configuration instruction comprises an apportionment rule parameter set based on a service demand, and the apportionment rule parameter at least comprises an apportionment dimension and an apportionment cause; and the application layer is used for acquiring the standardized allocation data set and the executable allocation rule set to obtain a multi-dimensional cost allocation accounting result. According to the embodiment of the invention, for a specific business scene of an enterprise, the fine management requirements of multiple business lines, multiple hierarchical departments and multiple cost centers can be met, and the cost effectiveness of each responsibility subject can be objectively reflected.

The invention discloses a cost and benefit evaluation method for a new energy power generation and heat supply project, and the method comprises the following steps: obtaining the cost of the new energy power generation and heat supply project, and calculating the comprehensive cost of the project; configuration parameters, required electricity consumption and subsidy income of the project main body are acquired, and the total income of the project is measured and calculated; carrying out financing scheme design in combination with the comprehensive cost of the project and the total income of the project; a plurality of yield indicators are obtained based on the financing scheme, and the project is evaluated and optimized according to the plurality of yield indicators. According to the method, the configuration parameters, the financing scheme, the cost income and dynamic optimization are organically combined, comprehensive, accurate and iteratively optimized evaluation of the new energy power generation heat supply project is realized, economic benefit maximization is realized, the feasibility of the project scheme and the scientificity of investment decision are remarkably improved, and the investment risk is effectively reduced.

The invention relates to a model parallel strategy searching method and device, computer equipment, a storage medium and a program product. The method comprises the following steps: initializing a cost estimator, a parameter optimizer and a real-time monitor; acquiring an initial parallel strategy by adopting a parameter optimizer; estimating the execution cost of the initial parallel strategy by adopting a cost estimator; according to the execution cost, a parameter optimizer is adopted to automatically search an optimal parallel strategy parameter based on a preset algorithm and modify the parameter of the initial parallel strategy, and a target parallel strategy is generated; issuing the target parallel strategy to a target model for training; a real-time monitor is adopted to monitor the target model, and whether the target parallel strategy is a parallel strategy adapting to the target model and the hardware state or not is determined; and when the target parallel strategy is the parallel strategy adapting to the target model and the hardware state, taking the target parallel strategy as the optimal parallel strategy. By adopting the method, the model parallel strategy which achieves the best balance between the cost benefit and the memory use can be automatically searched.

The invention discloses an intelligent monitoring method and system for a digital workshop production environment, and relates to the field of industrial control, and the main scheme is as follows: comparing different parameters in environmental data with corresponding thresholds in an environmental data threshold set, judging whether to execute a matched control instruction according to a comparison result, and if yes, executing the control instruction; adverse effects on the production process and the product quality due to environmental fluctuation are avoided; whether a matched control instruction is generated or not is judged according to the remote monitoring reliability H and the reliability threshold value, and the problem that the remote monitoring reliability is low is solved; power adjustment is performed on the equipment based on the equipment power adjustment coefficient, so that abrasion and faults of the equipment are reduced, and the performance and service life of the equipment are improved; the threshold value cost benefit and the optimization algorithm cost benefit are calculated and adjusted, the performance optimization method is judged by comparing the threshold value cost benefit and the optimization algorithm cost benefit, and the problem that performance evaluation cannot be carried out in time is solved.

This invention provides a method for predicting cattle weight and making optimal slaughter decisions using AI, comprising: collecting and processing 3D point cloud data of cattle to obtain a 3D model, and extracting body shape feature vectors; inputting the feature vectors into a deep neural network for mapping to obtain real-time weight data; processing the weight data and applying a neural Pareto algorithm for parameter calibration to obtain weight prediction data; collecting market price data and predicting prices; evaluating economic benefits based on weight prediction, price prediction, and cost data through comparative concept tree search; and finally mapping the evaluation results to a feature space and solving for the optimal slaughter decision scheme through similarity search and dynamic programming algorithms. This invention achieves contactless and accurate estimation of cattle weight, combined with market price prediction and cost-benefit analysis, providing a scientific basis for breeding decisions and significantly improving the economic benefits of breeding.

The invention provides a motor controller aging test method and device, which can accurately simulate an actual failure working condition and dynamically optimize a new strategy of aging duration so as to maximize the interception efficiency of an aging test on potential faults and realize the optimal balance of quality, cost and benefits under the constraint of limited cost. The method comprises the steps of formulating an alternating cycle working condition for an aging test based on a collected fault database of a motor controller; the historical fault database is obtained through fault data fed back by the market end motor controller, and the historical fault data comprises operation condition parameters when a fault occurs; the optimal aging duration is dynamically determined based on the alternating cycle working condition in combination with cost benefit analysis; the cost income analysis is used for evaluating the total cost under different aging durations, and the total cost is the sum of the aging test cost and the market maintenance cost estimated based on the failure probability; and performing a factory aging test on the to-be-tested motor controller according to the alternating cycle working condition and the optimal aging duration.

The application discloses a kind of network attack defense strategy automation cost benefit quantification method and device, the method first receives original alarm information and candidate defense strategy set, determines attack tactic stage by semantic analysis, and defense strategy group is mapped to standardization mitigation measure group;Again, a multi-cost index evaluation system is constructed to mitigation measure group, and the integrated cost probability distribution is aggregated by Gaussian modeling and hierarchical calibration entropy algorithm;For the basic income probability distribution of mitigation measure modeling, the effective income probability distribution is generated by combining the dynamic attack tactic weight calculated by control attenuation logic function, and the final effective income probability distribution is obtained by redundancy penalty;With the lower bound of confidence and the upper bound of cost confidence, the conservative cost benefit ratio is calculated as the quantitative score of defense strategy group.The application realizes the automation quantification of defense strategy cost benefit, to improve the standardization and accuracy of defense decision.

The invention discloses a coal power-new energy collaborative evaluation method and system based on a multi-dimensional index, and the method comprises the steps: obtaining the operation data of a power system, and carrying out the preprocessing of the data; constructing a multi-dimensional evaluation index system comprising a technical index, an economic index and an extrinsic index; performing normalization processing on the evaluation indexes, determining subjective weights, and obtaining comprehensive weights of the indexes through weighted fusion by combining objective weights determined by an entropy weight method; a weighted summation method is adopted to calculate a comprehensive score, and the coal power-new energy collaborative operation effect is graded and evaluated according to a scoring result; according to the method, a three-dimensional evaluation system including a technical index, an economic index and an external index is constructed, comprehensive evaluation is carried out on the coal power and new energy collaborative system from three key dimensions of system operation characteristics, cost benefits and environmental influences, and the problems that an existing evaluation method is single in dimension and incomplete in coverage are solved.