提出了一种综合考虑了训练误差和检验误差的评价神经模糊模型性能的误差性能指标。
A performance index of error was presented. This index is a kind of evaluation of neural fuzzy model performance and synthetically considered training error and checking error of NFS.
给出了应用实例。还研究了混沌参数与训练误差的关系，提出了混沌参数的调整步骤及应用。
And it studied relation between chaos mapping parameters and training error, puts forward chaos mapping parameter adjust steps and applications.
该技术首先对神经网络集成中的个体之间进行负相关处理提高个体的差异度，然后选择训练误差较小的个体来提高个体的精确度。
During the process of training, individual networks are trained using negative correlation learning to improve their diversity, and then networks with small errors are chosen to improve the accuracy.
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