A full-scene performance optimization quantitative method and system
By employing a quantitative method for full-scenario performance optimization, and utilizing a linear weighted model and an adjustable problem optimization formula, the problems of subjectivity, adaptability, and high cost in performance optimization in existing technologies are solved. This achieves full-scenario coverage and low-cost quantitative solutions, improving the measurability and flexibility of the solution.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- 薛梁
- Filing Date
- 2026-04-18
- Publication Date
- 2026-07-17
AI Technical Summary
Existing efficiency optimization methods suffer from problems such as strong subjectivity, narrow applicability, high implementation cost, difficulty in replication, and insufficient flexibility, making it impossible to achieve full-scenario coverage and low-cost quantitative solutions.
It adopts a quantitative method for full-scenario performance optimization, and through a closed-loop process of problem decomposition, requirement confirmation, scoring and quantification, modeling and solving, and solution matching, combined with a linear weighted model and a problem optimization formula with adjustable characteristics, it supports the demand side to add influencing factors and adjust formula parameters. It provides reverse derivation, hidden value mining of non-core dimensions, and adaptive iteration of fuzzy requirements, so as to achieve full customer coverage and batch solution output.
It achieves quantitative solutions for performance optimization, supports full-scenario adaptation, low licensing costs and custom extensions, improves the measurability and flexibility of the solution, and reduces implementation costs and replication difficulties.
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