摘要
神经网络 -遗传算法耦合的金融参数预测系统是利用智能模拟算法——遗传算法对神经网络预测金融参量系统的拓朴结构层间权系值进行优胜劣汰演化。证明了二者耦合能提高网络系统的学习效率和预测精度 ,成功实现了这两种智能模拟方法的集成耦合。
Neural network coupled with genetic algorithm is an intelligent simulating used in predicting the financial parameter system. Genetic algorithm predicts the coefficient of the topology layers in the neural network predicting the financial parameter system. This paper predicts business debt ratio. It proves that the combining technology improves the studying efficiency and the predicting precision of the network system to realize the combination of the two intelligent simulating methods.
出处
《武汉理工大学学报》
CAS
CSCD
2003年第11期103-106,共4页
Journal of Wuhan University of Technology
关键词
遗传算法
神经网络
拓朴结构
金融参数
耦合技术
genetic algorithms
neural network
topology structure
financial parameters
combining technology
