An optimization method for economic resource management based on intelligent decision-making

By collecting multi-source heterogeneous data, dividing dynamic resource pools and building nonlinear optimization models, the problems of inaccurate resource scheduling, inaccurate predictions and insufficient adaptability in traditional economic resource management have been solved, efficient resource utilization and rapid response have been achieved, and the stability and flexibility of the economic system have been improved.

CN120087722BActive Publication Date: 2025-10-03MINXI VOCATIONAL & TECHN COLLEGE
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Patent Information

Application Number
CN202510573044.1
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2025-05-06
Publication Date
2025-10-03
Estimated Expiration
2045-05-06

AI Technical Summary

Technical Problem

Traditional economic resource management methods are unable to cope with the complex and changing economic environment, are unable to achieve accurate scheduling and allocation of resources, have inaccurate forecasts, and lack adaptive learning capabilities, resulting in the coexistence of idle resources and shortages, and are unable to respond quickly to market and policy changes.

Method used

Collect multi-source heterogeneous data, divide the dynamic resource pool based on multi-dimensional feature analysis, build a nonlinear optimization model, dynamically update model parameters in combination with adaptive learning mechanism, optimize resource allocation path through multi-stage decision tree, correct allocation plan in real time, and use advanced algorithms to identify supply and demand contradictions and adjustment strategies.

Benefits of technology

It has achieved precise scheduling and allocation of resource management, improved resource utilization efficiency, reduced operating costs, enhanced the ability to respond to market and policy changes, and ensured the stable operation of the economic system.

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Abstract

The present invention relates to the technical field of economic resource management, and discloses an economic resource management optimization method based on intelligent decision-making. The method first collects multi-source heterogeneous data of the economic system, including resource stocks, demand fluctuations, etc. Then, based on multi-dimensional feature analysis, the dynamic resource pool is divided, and a nonlinear optimization model is constructed to predict changes in resource supply and demand to generate an allocation plan. Then, a multi-stage decision tree is used to optimize the allocation path, and the model parameters are updated through an adaptive learning mechanism according to market feedback and changes in constraints, and the allocation plan is corrected in real time. In addition, key technical details such as the elastic quota adjustment formula and the fuzzy clustering algorithm membership function are also given. The present invention can effectively integrate complex data, scientifically dispatch resources, accurately predict supply and demand, optimize allocation paths, adapt to environmental changes, significantly improve the efficiency and benefits of economic resource management, and provide scientific and reasonable resource management decision support for economic entities.
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