CLC number: TP18
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 0000-00-00
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LIU Ping, CHENG Yi-yu. AN IMPROVED GENETIC ALGORITHM FOR TRAINING LAYERED FEEDFORWARD NEURAL NETWORKS[J]. Journal of Zhejiang University Science A, 2000, 1(3): 322-326.
@article{title="AN IMPROVED GENETIC ALGORITHM FOR TRAINING LAYERED FEEDFORWARD NEURAL NETWORKS",
author="LIU Ping, CHENG Yi-yu",
journal="Journal of Zhejiang University Science A",
volume="1",
number="3",
pages="322-326",
year="2000",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.2000.0322"
}
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%A LIU Ping
%A CHENG Yi-yu
%J Journal of Zhejiang University SCIENCE A
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%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.2000.0322
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T1 - AN IMPROVED GENETIC ALGORITHM FOR TRAINING LAYERED FEEDFORWARD NEURAL NETWORKS
A1 - LIU Ping
A1 - CHENG Yi-yu
J0 - Journal of Zhejiang University Science A
VL - 1
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SP - 322
EP - 326
%@ 1869-1951
Y1 - 2000
PB - Zhejiang University Press & Springer
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DOI - 10.1631/jzus.2000.0322
Abstract: The new genetic algorithm for training layered feedforward neural networks proposed here uses a mutation operator for performing the search behaviors of local optimization. Combining the random restart method with the local search technique, the algorithm can converge asymptotically to the optimal solution. Test with a practical example showed that the improved genetic algorithm is more efficient than the conventional genetic algorithm.
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