A robust firefly algorithm with backpropagation neural networks for solving hydrogeneration prediction
Hydrogeneration prediction typically has composite structures such as nonlinearity, non-stationarity, and fluctuation, which converts its predicting to be very tough. The applications of backpropagation neural network (BPNN) are very various and saturated. The linear threshold part of the BPNN produ...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Springer
2018
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/23312/ http://umpir.ump.edu.my/id/eprint/23312/ http://umpir.ump.edu.my/id/eprint/23312/ http://umpir.ump.edu.my/id/eprint/23312/1/A%20robust%20firefly%20algorithm%20with%20backpropagation%20neural%20networks%20for%20solving%20hydrogeneration%20prediction%20-%20s00202-018-0732-6.pdf |
Internet
http://umpir.ump.edu.my/id/eprint/23312/http://umpir.ump.edu.my/id/eprint/23312/
http://umpir.ump.edu.my/id/eprint/23312/
http://umpir.ump.edu.my/id/eprint/23312/1/A%20robust%20firefly%20algorithm%20with%20backpropagation%20neural%20networks%20for%20solving%20hydrogeneration%20prediction%20-%20s00202-018-0732-6.pdf