Power public opinion data-driven work deployment adaptive optimization method and system

By using an adaptive optimization method driven by power public opinion data, a public opinion knowledge graph and a multi-objective model are constructed to generate the optimal work deployment plan. This solves the problem of the disconnect between public opinion monitoring and business deployment in power companies, and realizes adaptive resource scheduling and efficient response.

CN121707052APending Publication Date: 2026-03-20FUJIAN YIRONG INFORMATION TECH
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Patent Information

Application Number
CN202511877350.0
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-12-12
Publication Date
2026-03-20

AI Technical Summary

Technical Problem

Power companies' work deployment methods suffer from problems such as a disconnect between public opinion monitoring and business deployment, insufficient adaptability of resource scheduling, one-sided analytical perspectives, and low execution efficiency, making it difficult to cope with changes in the urgency of public opinion and dynamically adjust resources.

Method used

By using an adaptive optimization method driven by power public opinion data, a public opinion knowledge graph is constructed to obtain a comprehensive public opinion risk index. Combined with a multi-objective business deployment model, the optimal work deployment plan is generated using an adaptive optimization algorithm. Decision support is provided through a visual dashboard, establishing a closed-loop mechanism of perception-decision-execution-feedback.

Benefits of technology

It enables automatic identification of high-risk events before they escalate, proactive intervention, more precise resource allocation, optimized cross-departmental task and resource matching, improved response efficiency and user satisfaction, and the construction of an adaptive resource scheduling mechanism.

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Abstract

The invention relates to an electric power public opinion data driven work deployment adaptive optimization method and system, and the method comprises the following steps: S1, obtaining multi-source data related to electric power public opinions, filtering noise data, forming a standardized data set, and constructing a unified public opinion data pool; s2, constructing a public opinion knowledge graph, and obtaining a comprehensive public opinion risk index; s3, constructing a multi-target service deployment adaptive optimization model; s4, according to the multi-target service deployment adaptive optimization model, obtaining an optimal work deployment scheme based on a scheme solving and generating method of an adaptive optimization algorithm; and S5, according to the optimal work deployment scheme, pushing the optimal work deployment scheme to a decision maker through a visual billboard, tracking the whole execution process of the scheme, and feeding back an execution result and newly added public opinion data to the step S1. Through real-time public opinion analysis, high-risk events are automatically identified before event expansion, active intervention is realized, and a traditional passive complaint waiting mode is changed.
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