Based on expatiated the basic structure model and some general improved algorithms of BP neural network, this paper brings forward a new self-organization learning algorithm.
介绍了BP网络的基本结构模型与常见改进算法，在此基础上提出了一种新型的结构自组织BP网络算法。
The application shows that the algorithms simplify the computing complexity of process neural networks, and raise the efficiency of the network learning and the adaptability to real problem resolving.
应用表明，算法简化了过程神经网络的计算复杂度，提高了网络学习效率和对实际问题求解的适应性。
Mostly used methods are introduced in detail, including fuzzy method, rough sets theory, cloud theory, evidence theory, artificial neural networks, genetic algorithms and induction learning.
详细介绍了数据挖掘技术的常用方法，包括模糊理论、粗糙集理论、云理论、证据理论、人工神经网络、遗传算法以及归纳学习。
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