An empirical study of impact of crossover operators on the performance of non-binary genetic algorithm based neural approaches for classification

Authors:
Parag C. Pendharkar;James A. Rodger
Affiliations:
Information Systems, School of Business Administration, Penn State University at Harrisburg, 777 West Harrisburg Pike, Middletown, PA;MIS and Decision Sciences, Eberly College of Business Administration, Indiana University of Pennsylvania, Indiana, PA
Venue:
Computers and Operations Research
Year:
2004

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Abstract

We study the performance of genetic algorithm (GA) based artificial neural network (ANN) for different crossover operators. We use simulated and real life data to test the performance of GA-based ANN. Our results indicate that arithmetic crossover operator may be a suitable crossover operator for GA based ANN.