Nonlinear feature extraction using a neuro genetic hybrid
作者： Yung-Keun Kwon , Byung-Ro Moon
关键词: Artificial neural network 、 Deep learning 、 Computer science 、 Types of artificial neural networks 、 Recurrent neural network 、 Feature extraction 、 Machine learning 、 Pattern recognition 、 Stochastic neural network 、 Artificial intelligence 、 Probabilistic neural network 、 Neural gas 、 Feature vector 、 Feedforward neural network 、 Time delay neural network 、 Genetic algorithm
摘要: Feature extraction is a process that extracts salient features from observed variables. It considered promising alternative to overcome the problems of weight and structure optimization in artificial neural networks. There were many nonlinear feature methods using networks but they still have same difficulties arisen fixed network topology. In this paper, we propose novel combination genetic algorithm feedforward for extraction. The evolves space by utilizing characteristics hidden neurons. improved remarkably performance on number real world regression classification problems.
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sci-hub.se 参考文章(37)
Teuvo Kohonen, Self-organized formation of topologically correct feature maps Biological Cybernetics. ,vol. 43, pp. 509- 521 ,(1988) , 10.1007/BF00337288
Oded Maimon, Merrick L. Furst, Shai Oliker, A Distributed Genetic Algorithm for Neural Network Design and Training. Complex Systems. ,vol. 6, ,(1992)
David S. Touretzky, Dean A. Pomerleau, What's hidden in the hidden layers? BYTE archive. ,vol. 14, pp. 227- 233 ,(1989)
H. Kitnano, Designing Neural Networks Using Genetic Algorithms with Graph Generation System Complex Systems. ,vol. 4, ,(1990)
Dirk Thierens, Johan Suykens, Joos Vandewalle, Bart De Moor, Genetic Weight Optimization of a Feedforward Neural Network Controller international conference on artificial neural networks. pp. 658- 663 ,(1993) , 10.1007/978-3-7091-7533-0_95
Chris Harris, Martin Brown, Neurofuzzy adaptive modelling and control ,(1994)
William F. Punch, Richard J. Enbody, Paul D. Hovland, Min Pei, Erik D. Goodman, Lai Chia-Shun, Further Research on Feature Selection and Classification Using Genetic Algorithms international conference on genetic algorithms. pp. 557- 564 ,(1993)
David E. Rumelhart, Geoffrey E. Hinton, Ronald J. Williams, Learning representations by back-propagating errors Nature. ,vol. 323, pp. 696- 699 ,(1988) , 10.1038/323533A0
Byung Ro Moon, Yung-Keun Kwon, Sung-Deok Hong, A Genetic Hybrid For Critical Heat Flux Function Approximation genetic and evolutionary computation conference. pp. 1119- 1125 ,(2002)
Peter M. Todd, Shailesh U. Hegde, Geoffrey F. Miller, Designing neural networks using genetic algorithms international conference on genetic algorithms. pp. 379- 384 ,(1989)