Method for determining mixing optimizing of artificial fish stock and particle swarm

A technology of artificial fish school and determination method, applied in the field of surveying and mapping, which can solve the problems of slow convergence speed and low precision.

Inactive Publication Date: 2014-06-25
HOHAI UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0002] The artificial fish swarm algorithm has a good ability to obtain the global extremum, and has the advantages of insensitivity to disposal and parameter selection, strong robustness, simplicity, and easy operation. It has been used in neural networks, pattern recognition, parameter estimation, identification methods, etc. It can be used in various aspects, but the traditional calculation method converges slowly and the accuracy is not high

Method used

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  • Method for determining mixing optimizing of artificial fish stock and particle swarm
  • Method for determining mixing optimizing of artificial fish stock and particle swarm
  • Method for determining mixing optimizing of artificial fish stock and particle swarm

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0065] x 2 + y 2 + z 2 - 3 = 0 x 2 + y 2 + xy + x + y - 5 = 0 x + y + z - 3 = 0

[0066] This embodiment is implemented by p...

Embodiment 2

[0075] sin x 1 + x 2 = 2.2 4 x 1 + x 2 2 = 7

[0076] This embodiment is implemented by programming under matlab, using the basic artificial fish swarm algorithm (AFSA) and the determination method of artificial fish swarm and particle swarm optimization (AF-PSO) to solve the problem. The parameters are set as follows, the number of individuals of artificial fish swarm and particle swarm is N=50, the perception range of artificial fish Visual=2, the step size Step=0.3, th...

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Abstract

The invention discloses a method for determining mixing optimizing of an artificial fish stock and a particle swarm. The method comprises the step of initializing the artificial fish stock and the particle swarm; the step of calculating the fitness function values of all individuals; the step of judging whether fitness values of all the individuals of the two stocks meet the boundary conditions or not, wherein if not, the values are updated again until the fitness values of all the individuals meet the boundary conditions; the step of executing the corresponding algorithms of the two stocks to obtain new stocks; the step of serving the individual with the minimum fitness values of the two stocks as the optimal solution to be posted on a bulletin board Best; the step of selecting 10 percent of the individuals with the poor fitness in the two stocks to carry out jump and update the values; the step of circularly updating Best on the bulletin board until Best is smaller than the limit of error. The method has the advantages of being high convergence rate and solving precision.

Description

technical field [0001] The invention relates to surveying and mapping, in particular to a method for determining mixed optimization of artificial fish swarms and particle swarms. Background technique [0002] The artificial fish swarm algorithm has a good ability to obtain the global extremum, and has the advantages of insensitivity to disposal and parameter selection, strong robustness, simplicity, and easy operation. It has been used in neural networks, pattern recognition, parameter estimation, identification methods, etc. It can be applied in various aspects, but the traditional calculation method converges slowly and the accuracy is not high. Contents of the invention [0003] Purpose of the invention: The purpose of the invention is to solve the deficiencies in the prior art and provide a method for determining the mixed optimization of artificial fish swarm and particle swarm optimization. [0004] Technical solution: a method for determining the mixed optimization...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04
Inventor 岳建平刘斌张涛顾景强曾宝庆梁子亮
Owner HOHAI UNIV
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