提出一种关于多层前向神经网络结构的混沌优化设计方法。
The optimization design method is proposed for feed-forward neural network structure by means of chaos ergodicity and randomicity.
在应用人工神经网络时，采用基于相关分析法的节点删除法来优化网络结构提高网络性能。
During the use of the artificial neural network some nodes were deleted to optimize the network based on the correlation analytical theory.
由于动态神经网络结构及权值确定困难，采用二进制与实数编码相结合的联合编码，用遗传算法优化得到神经网络结构及对应权值。
To rise above the difficulty of determining NN's structure and weights, the GA optimization algorithm is used to get them by combining binary encoding with real encoding.
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