Neural Network Structure Design Using Genetic Algorithms

DOI Web Site Web Site 1 Citations 4 References

Bibliographic Information

Other Title
  • 遺伝的アルゴリズムによるニューラルネットワークの構造決定
  • イデンテキ アルゴリズム ニ ヨル ニューラルネットワーク ノ コウゾウ ケッ

Search this article

Abstract

For the purpose of automatic and effective neural network structure design, a designing method is proposed based on Genetic Algorithms (GA). Neural Network structures are encoded on chromosomes in such a way that a number of different but related network structures result by changing a parameter in the decoding process. The GA finds an optimal chromosome that provides good network structures for a family of data sets. When a change takes place in the environment around the neural network, by changing the parameter, we can obtain a new neural network suitable for the new environment without re-running the GA again.<br>The proposed method is described by using, as an example, a problem of finding good neural network structures for data sets with different noise magnitudes. To obtain an accurate but non-overfitted neural network for the noisy data set, we introduce a relevant fitness function, a method for noise magnitude estimation, and a systematic way to determine the control parameter value of the decoding process. By incorporating these techniques in the network structure designing method mentioned above, we obtain a neural network which has a good generalization ability for each of data sets with different noise magnitudes.

Journal

Citations (1)*help

See more

References(4)*help

See more

Keywords

Details 詳細情報について

Report a problem

Back to top