Then some defects such as slow convergence rate and getting into local minimum in BP algorithm are pointed out, and the root of the defects is presented.
分析了BP算法的基本原理，指出了BP算法具有收敛速度慢、易陷入局部极小点等缺陷以及这些缺陷产生的根源。
In the individual credit evaluation part, it quantifies all kinds of scattered data, and to improve BP algorithm it USES local self-adaptive study rate algorithm.
在个人信用评估部分中，对所有的离散数据进行量化处理，然后使用局部学习率自适应算法，对BP算法加以改进。
The algorithm can get global minimum easily with a wide variety of functions of hidden neurons, and no problems such as local minima and slow rate of convergence are suffered like BP algorithm.
新算法选择很广一类的隐层神经元函数，可以直接求得全局最小点，不存在BP算法的局部极小、收敛速度慢等问题。
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