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Hypersphere search algorithm based on differential evolution

A technology of differential evolution and ball search, applied in the field of hypersphere search algorithm, to achieve the effect of enhancing accuracy, strengthening global optimization ability, and clear process

Pending Publication Date: 2020-02-04
CRRC CHANGCHUN RAILWAY VEHICLES CO LTD
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Problems solved by technology

Analytical methods usually require mathematical models that can correspond to existing mathematical calculation methods, and problems that cannot be solved by current mathematical analytical optimization algorithms need to be simplified, otherwise there is nothing they can do

Method used

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  • Hypersphere search algorithm based on differential evolution
  • Hypersphere search algorithm based on differential evolution
  • Hypersphere search algorithm based on differential evolution

Examples

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Embodiment Construction

[0015] Such as figure 1 As shown, a hypersphere search algorithm based on differential evolution includes the following steps:

[0016] Define the initial population number N pop , the number of hypersphere centers N SC , the upper and lower limits of the hypersphere search radius r min , r max , the hyperball movement angle change probability Pr angle , Differential evolutionary crossover probability MR, differential evolutionary mutation probability CR. Taking finding the minimum value in the search space as an example, the process of the algorithm is introduced, and the main steps involved are as follows:

[0017] Step1 initialization

[0018] Step1.1 Define the initial population number N pop , the number of hypersphere centers N SC , the upper and lower limits of the hypersphere search radius r max , r min , the hyperball movement angle change probability Pr angle , differential evolution crossover probability MR, differential evolution mutation probability CR;...

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Abstract

The invention discloses a hypersphere search algorithm based on differential evolution. An initial population number Npop, the number of hypersphere centers NSC; the upper and lower limits rmin and rmax of the hypersphere searching radius, a hypersphere motion angle change probability Prangle, a differential evolution crossover probability MR and a differential evolution mutation probability CR are defined, the algorithm comprise six steps of algorithm initialization, result optimal movement, differential evolution, virtual particle recovery, hypersphere center re-determination and judgment convergence, the six steps are closely related, the overall algorithm design is simplified, the process is clear, and the practicability is high. According to the algorithm, under the condition that theoptimal solution is not lost, the global search capability is improved, the accuracy of the obtained solution is enhanced, and a new optimization technology is provided for the field of rail transit.

Description

technical field [0001] The invention relates to the field of meta-heuristic intelligent optimization, in particular to a hypersphere search algorithm based on differential evolution. Background technique [0002] Optimization problems are always an unavoidable class of problems in engineering practice and scientific research. The solution to the optimization problem mainly includes two methods: analytical method and intelligent optimization algorithm. Analytical methods usually require mathematical models that can correspond to existing mathematical calculation methods, and problems that cannot be solved by current mathematical analysis and optimization algorithms need to be simplified, otherwise there is nothing they can do. Contents of the invention [0003] The purpose of the present invention is to provide a hypersphere search algorithm based on differential evolution. The proposed hypersphere search algorithm based on differential evolution can improve the global sea...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/00G06N7/00
CPCG06N3/006G06N7/01
Inventor 赵海波齐玉文李恩龙王艳秋
Owner CRRC CHANGCHUN RAILWAY VEHICLES CO LTD
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