基于BP-GA的融合算法实现

搜索和寻优是控制、预测等应用技术的基础。在人工智能领域，人工神经网络和遗传算法是解决搜索和寻优这2个问题的基本方法。对BP算法和遗传算法进行了研究，指出了其优缺点；研究了传统的将BP和GA结合起来求解问题的几种方式。鉴于这几种方式存在的实际应用缺陷，提出了一种新型的融合算法，阐述了其基本原理，给出了设计流程图，并详细研究了该融合算法的设计步骤。最后，运用示例验证该算法。

The Realization for the Hybrid Algorithm Based on BP-GA

In the realm of the artificial intelligence, search solution and optimization algorithm, whose basic method are artificial neural network and genetic algorithms, are the fundament for the technologic application of control and forecast. The paper researches the elementary content for the artificial neural network and genetic algorithms. Meanwhile, it studies the traditional integration for two kinds of arithmetic. Because the methods have many disadvantages in application, a new sort of hybrid algorithm is put forward. The paper not only expatiates on the keystone for this method, but draws upon the design flow chart. Then, its design steps are explicated. Lastly, an example is illustrated to justify this method.