带内复制算子的遗传算法在递归神经网络中的结构化学习

Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97) Pub Date : 1997-04-13 DOI:10.1109/ICEC.1997.592395

T. Kumagai, M. Wada, S. Mikami, R. Hashimoto

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引用次数: 9

摘要

我们编写了一个遗传算法，该算法使用内部复制算子进行循环神经网络学习。内部复制操作者将基因的一部分复制到同一基因的另一部分。我们证明了该算法加速了学习。我们还证明了内部复制操作符在网络中组织结构。这种有组织的结构提高了系统的学习能力，使其易于获取一组极限环成为可能。

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Structured learning in recurrent neural network using genetic algorithm with internal copy operator

We compose a genetic algorithm that uses an internal copy operator for recurrent neural network learning. The internal copy operator copies one part of a gene to another part of the same gene. We show that the proposed algorithm accelerates learning. We also show that the internal copy operator organizes the structure in the network. The organized structure improves the learning ability and makes it possible to acquire a set of limit cycles easily.

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Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97)

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