FKCN优化的RBF网络在降水量预测中的应用

Rainfall forecasting using RBFNN optimized by FKCN

旱涝灾害的预测预报是目前世界上公认的难点问题之一 ,它不仅具有重要的现实意义 ,同时在理论上也是一个典型的非偏差时间序列预测问题。而降水量是影响旱涝灾害的一个重要因素。该文采用 FKCN优化的 RBF网络对安徽省蚌埠市汛期的降水量进行了预测 ,针对降水数据的特点 ,提出了一种简单有效的数据预处理方法 。

Drought and waterlogging damage prediction has been one of the most challenging problems around the world, and it is not only practically valuable in meteorology, but also a typically 'unbiased' time series forecasting problem in scientific researches. Rainfall is an important factor of the damage.This paper uses RBF neural network optimized by FKCN to predict the rainfall of Bengbu area.The present work provides an easy and effective method to preprocess the data. A good result is obtained.