摘要
用基于GA的RBF网络构成非线性时间序列预测器 ,针对灾害因素中的降雨量、最高水位、最大流量等进行预测。在运用GA的过程中 ,针对RBF的网络结构提出了与以往不同的编码方式 ,使得整个编码过程简单有效 ,而且符合RBF网络本身的特性。
We use RBF neural network based on GA to make up a nonlinear time series predication implement, which is used to predict the disaster elements, such as the precipitation, the highest water level and the biggest flow, etc. We advance a new code way in accordance with the RBF neural network, which not only made the whole code process simply and efficient but also accord with the characteristic of RBFNN.
出处
《计算机应用》
CSCD
北大核心
2001年第1期7-9,共3页
journal of Computer Applications