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ZJUS-A
Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering)  2000, Vol. 1 Issue (3): 322-326    DOI: 10.1631/jzus.2000.0322
Science & Engineering     
AN IMPROVED GENETIC ALGORITHM FOR TRAINING LAYERED FEEDFORWARD NEURAL NETWORKS
LIU Ping, CHENG Yi-yu
Dept.of Chemical Engineering, Zhejiang University, Hangzhou, 310027, China
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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.

Key words： artificial neural network      genetic algorithms      layered feedforward neural networks     
Received: 10 May 1999     
CLC:  TP18  
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LIU Ping
CHENG Yi-yu
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LIU Ping, CHENG Yi-yu. AN IMPROVED GENETIC ALGORITHM FOR TRAINING LAYERED FEEDFORWARD NEURAL NETWORKS. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2000, 1(3): 322-326.

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http://www.zjujournals.com/xueshu/zjus-a/10.1631/jzus.2000.0322     OR     http://www.zjujournals.com/xueshu/zjus-a/Y2000/V1/I3/322

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