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Improvement And Application Of Symbiotic Organisms Search Algorithm

Posted on:2019-02-20Degree:MasterType:Thesis
Country:ChinaCandidate:F H MiaoFull Text:PDF
GTID:2428330545468387Subject:Computer application technology
Abstract/Summary:PDF Full Text Request
The symbiotic organisms search algorithm mainly simulates the symbiotic relationship between organisms in nature to achieve the search for optimal individuals.In nature,symbiotic relationships usually include mutualism,commensalism,and parasitism.The symbiotic organisms search algorithm has the obvious advantage that it does not need specific control parameters in the process of algorithm implementation.The algorithm has simple structure,easy to use and to popularize.However,with the deepening of research,the researchers found that the convergence accuracy of the symbiotic organisms search algorithm is not high and the convergence rate is slow in the later period.This paper aims at improving the existing problems of basic symbiotic organisms search algorithm,and applies it to more practical problems,and extends its application scope.The main work has the following three aspects:(1)The idea of complex coding is introduced into the symbiotic organisms search algorithm.In the CSOS algorithm,the structure of the real and imaginary parts of the complex code is introduced into the symbiotic organisms search algorithm,and the two-dimensional coding space of the complex code is used to map the real-coded one-dimensional coding space.We use real and imaginary parts to collectively represent a biological individual in the population,and the real and imaginary parts are updated separately to find the optimal value of the algorithm.This haploid structure expands the information contained in the individual genes of the organism in the symbiotic organisms search algorithm,increases the biodiversity of the individual in the population,expand the search scope of the group,improves the possibility of obtaining the optimal solution,and enhances the optimization of the algorithm ability.(2)In order to solve the problem of low convergence accuracy of the basic symbiotic organisms search algorithm in UCAV route planning,the simplex method is introduced to improve the original algorithm.As a kind of random variation strategy,the simplex method can increase the diversity of the population and improve the ability of the algorithm to explore and exploit,and effectively avoid premature falling into local optimum.The algorithm of simplex symbiotic organisms search is used to study the path planning problem of UCAV with random variable area.This algorithm is more suitable for solving UCAV route planning problem.(3)Compared with the traditional integer order fuzzy controller,the fractional order fuzzy controller increases the control parameters,which is difficult for the solution of parameter calibration.The fuzzy controller parameters calibration value have obvious influence,for the performance of the controller is based on this,this paper introduces a symbiotic organisms search algorithm to optimize the parameter calibration of the fuzzy controller,the control parameters of the optimal control,to improve the performance of the fractional order fuzzy controller.The simulation results show that the symbiotic organisms search algorithm has a good effect on the parameter calibration and optimization of the fuzzy controller.
Keywords/Search Tags:The symbiotic organisms search algorithm, Complex coding, The simplex method, Unmanned Combat Aerial Vehicle Route Planning, Evolutionary calibration of fractional fuzzy controllers, Meta-heuristic algorithm
PDF Full Text Request
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