DocumentCode
394424
Title
Disruption analysis for neural network topology evolution systems
Author
Dàvila, Jaime J.
Author_Institution
Sch. of Cognitive Sci., Hampshire Coll., Amherst, MA, USA
Volume
4
fYear
2002
fDate
18-22 Nov. 2002
Firstpage
1920
Abstract
This paper presents a method for analyzing GA effectiveness for the evolution of neural networks. The analysis is based on the schemata of the (phenotype) neural network being evolved, as opposed to the traditional method of analyzing schemata disruptions at the genotype level. Comparisons between the two types of analysis are made. Empirical data is presented that indicates the greater validity of the analysis at the phenotype level.
Keywords
genetic algorithms; multilayer perceptrons; neural net architecture; topology; disruption analysis; genetic algorithms; hidden layers; multilayer network; neural network topology evolution systems; phenotype level; schemata disruptions; Algorithm design and analysis; Cellular neural networks; Cognitive science; Educational institutions; Genetic algorithms; Genetic mutations; Network topology; Neural networks; System testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Information Processing, 2002. ICONIP '02. Proceedings of the 9th International Conference on
Print_ISBN
981-04-7524-1
Type
conf
DOI
10.1109/ICONIP.2002.1199008
Filename
1199008
Link To Document