基于小生境技术的神经网络进化集成

针对目前神经网络集成方法中生成个体网络差异度小、集成泛化能力较差等缺点，提出一种基于小生境技术的神经网络进化集成方法。利用小生境技术在增加进化群体的多样性、提高进化局部搜索能力方面的良好性能，通过个体间相似程度的共享函数来调整神经网络集成中个体网络的适应度，再依据调整后的新适应度进行选择，以维护群体的多样性，得到多样性的个体网络。理论分析和实验结果表明，该方法能有效生成差异度较大的个体网络，提高神经网络集成系统的泛化能力与计算精度。

Evolutionary ensemble of neural network based on niche technology

In view of the current problems that neural network ensemble generates individual networks with low difference degree and its poor generalization ability, a method of evolutionary ensemble of neural network based on niche technique was proposed. Niche technique's good performance was used in increasing population diversity and improving local search capability of evolution, and the similarity degree's sharing function among individuals was adopted to adjust individual network's fitness. Then the individuals were selected according to the new adjusted fitness to get individual network with diversity. Theoretical analysis and experimental results show that this method can generate individual network with great difference degree and can improve the generalization ability and calculation accuracy of neural network ensemble system.