A Preliminary Survey on Genetic Algorithm Techniques

  IJCTT-book-cover
 
International Journal of Computer Trends and Technology (IJCTT)          
 
© 2015 by IJCTT Journal
Volume-23 Number-4
Year of Publication : 2015
Authors : Mayilvaganan M, Geethamani G.S
  10.14445/22312803/IJCTT-V23P136

MLA

Mayilvaganan M, Geethamani G.S "A Preliminary Survey on Genetic Algorithm Techniques". International Journal of Computer Trends and Technology (IJCTT) V23(4):175-179, May 2015. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.

Abstract -
In recent years, data mining and Genetic algorithms is an essential aspect for searching and generating association rules among the large number of itemsets. Genetic algorithms maintain a population pool of candidate solutions called strings or chromosomes. Each chromosome p is a collection of building blocks known as genes, which are instantiated with values from a finite domain. Associated with each chromosome is a fitness value which is determined by a user defined function, called the fitness function. The performance of a GA is dependent on the genetic operators in general and on the type of crossover operator, in particular. Effective crossover in a GA is achieved through establishing the optimum relationship between the crossover and the search problem itself. In this paper, an preliminary studies have been carried out to enable the researcher to identify the various genetic algorithm methods.

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Keywords
Data Mining, Genetic Algorithm, itesets,chromosomes,crossover,fitness function.