神经式网络

Firstly, population partition methodology is presented by combining characteristics of both the cooperative co-evolutionary genetic algorithm and the neural network. Secondly, a novel mixed encoding method is also put forward to perform synchronal optimization of structure and weights of the neural network. Proper crossover and mutation operators were designed based on the encoding method. Next, a novel structure optimization technique is given according to the relationship among encoding, representation and cooperative group. Representative individual selecting and fitness evaluating are given.

首先，结合合作式协同进化遗传算法本身特性和神经网络特点，给出种群分割方法；其次，为了实现结构和权值的同步优化，提出一种新的混合编码方法，并根据该混合编码方法设计新的交叉和变异算子；然后，根据编码结构、代表个体和合作团体之间的关系，提出一种新的结构优化方法；再次，给出进化过程所需代表个体选择、适应度构造方法等。

The split between the two groups can hardly be papered over.

这两个团体间的分歧难以掩饰。

This approach not only encourages a greater number of responses, but minimizes the likelihood of stale groupthink.

这种做法不仅鼓励了更多的反应，而且减少跟风的可能性。