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Huang, Chien-Yu, Wang, I-Chiang, Chen, Tien-Hui (2013) A Robust Design Approach for GA-based Back Propagation Neural Networks Designed to Classify Data of Different Types. Journal of Applied Sciences, 13. 242-251 doi:10.3923/jas.2013.242.251

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Reference TypeJournal (article/letter/editorial)
TitleA Robust Design Approach for GA-based Back Propagation Neural Networks Designed to Classify Data of Different Types
JournalJournal of Applied Sciences
AuthorsHuang, Chien-YuAuthor
Wang, I-ChiangAuthor
Chen, Tien-HuiAuthor
Year2013 (February 1)Volume13
PublisherScience Alert
DOIdoi:10.3923/jas.2013.242.251Search in ResearchGate
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Mindat Ref. ID10343057Long-form Identifiermindat:1:5:10343057:9
GUID0
Full ReferenceHuang, Chien-Yu, Wang, I-Chiang, Chen, Tien-Hui (2013) A Robust Design Approach for GA-based Back Propagation Neural Networks Designed to Classify Data of Different Types. Journal of Applied Sciences, 13. 242-251 doi:10.3923/jas.2013.242.251
Plain TextHuang, Chien-Yu, Wang, I-Chiang, Chen, Tien-Hui (2013) A Robust Design Approach for GA-based Back Propagation Neural Networks Designed to Classify Data of Different Types. Journal of Applied Sciences, 13. 242-251 doi:10.3923/jas.2013.242.251
In(n.d.) Journal of Applied Sciences Vol. 13. Science Alert

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