期刊名称：International Journal of Engineering and Computer Science
印刷版ISSN：2319-7242
出版年度：2016
卷号：5
期号：1
页码：15428-15431
DOI：10.18535/Ijecs/v5i1.5
出版社：IJECS
摘要：The basic idea behind this proposed method is to analyze the genetic cross over techniquesusing roulette wheel selection and steady state selection algorithm.The proposed algorithm is applied to find the genetic operators which are termed as mutation, crossover andselection in large dataset. The proposed technique is very useful to analyse the impact of genetic crossovertechniques in random population of chromosomes.After estimating the genetic crossover technique, the efficiency of the roulette wheel and steady stateselection algorithm are estimated. After estimating the efficiency of both algorithms, there is a need tocompare the efficiency of roulette wheel and steady state selection algorithm based on the initial population.The extracted rules and analyzed results are graphically demonstrated. The performance is analyzed basedon the different number of instances in large data set
