Genetic Algorithm-Neural Network (GANN): a study of neural network activation functions and depth of genetic algorithm search applied to feature selection

Author:

Tong Dong Ling,Mintram Robert

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Software

Reference17 articles.

1. Beiko RG, Charlebois RL (2005) GANN: genetic algorithm neural networks for the detection of conserved combinations of features in DNA. BMC Bioinformatics 6:36

2. Bevilacqua V, Mastronardi G, Menolascina F, Paradiso A, Tommasi S (2006) Genetic algorithms and artificial neural networks in microarray data analysis: a distributed approach. Eng Lett Spec Issue Bioinformatics 13(3):335–343

3. Cartwright H (2008) Using artificial intelligence in chemistry and biology: A practical guide. In: Chapter Evolutionary Algorithms, CRC Press, Taylor & Francis Group, Boca Raton, London pp 113–172

4. Cho HS, Kim TS, Wee JW, Jeon SM, Lee CH (2003) cDNA microarray data based classification of cancers using neural networks and genetic algorithms. In Nanotech’03: Nanotechnology Conference and Trade Show, proceedings, vol 1

5. DeJong KA, Spears WM (1991) An analysis of the interacting roles of population size and crossover in genetic algorithms. In: Schwefel HP, Männer R (eds) PPSN’91: first Workshop on Parallel Problem Solving from Nature, proceedings, volume 496 of Lecture Notes in Computer Science, Springer, Berlin pp 38–47

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