NeuroEvolutionary Feature Selection Using NEAT

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Journal of Software Engineering and Applications

ISSN Print: 1945-3116
ISSN Online: 1945-3124

Website: https://www.scirp.org/journal/jsea
E-mail: jsea@scirp.org

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Submission

"NeuroEvolutionary Feature Selection Using NEAT"
written by Soroosh Sohangir, Shahram Rahimi, Bidyut Gupta,
published by Journal of Software Engineering and Applications, Vol.7 No.7, 2014

has been cited by the following article(s):

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[1]	Neuroevolution as a tool for microarray gene expression pattern identification in cancer research
	2019

[2]	KLASIFIKASI GAMBAR PADA GOOGLE QUICK DRAW MENGGUNAKAN CONVOLUTIONAL NEURAL NETWORK DAN NEUROEVOLUTION OF AUGMENTING …
	2019

[3]	Microarray Classification and Gene Selection with FS-NEAT
	2018

[4]	NEAT-FLEX: Predicting the conformational flexibility of amino acids using neuroevolution of augmenting topologies
	Journal of bioinformatics and computational biology, 2017

[5]	Predicting protein structural features with NeuroEvolution of Augmenting Topologies
	2016

[6]	Learning neural network structures with ant colony algorithms
	Swarm Intelligence, 2015

[7]	Machine learning algorithm performance optimization: Solving issues of big data analysis
	ProQuest Dissertations Publishing, 2015

[8]	The State of Evolutionary Computation

[1]	Neuroevolution as a tool for microarray gene expression pattern identification in cancer research Journal of Biomedical Informatics, 2019 DOI:10.1016/j.jbi.2018.11.013

[2]	Microarray Classification and Gene Selection with FS-NEAT 2018 IEEE Congress on Evolutionary Computation (CEC), 2018 DOI:10.1109/CEC.2018.8477813

[3]	NEAT-FLEX: Predicting the conformational flexibility of amino acids using neuroevolution of augmenting topologies Journal of Bioinformatics and Computational Biology, 2017 DOI:10.1142/S0219720017500093

[4]	Predicting protein structural features with NeuroEvolution of Augmenting Topologies 2016 International Joint Conference on Neural Networks (IJCNN), 2016 DOI:10.1109/IJCNN.2016.7727291

[5]	Learning neural network structures with ant colony algorithms Swarm Intelligence, 2015 DOI:10.1007/s11721-015-0112-z