天津工业大学学报2012，Vol.31Issue(4)：68-71,4.
基于迟滞神经网络的风速时间序列预测
Prediction of wind speed time series based on hysteretic neural network
摘要
Abstract
In order to improve the prediction performance of the wind speed time series, a new prediction method based on hysteretic neural nctwork is proposed. Hysteretic characteristic which can make history input change the current response of the neural network is brought into the neural network by changing activation function. Therefore, 1he utilization rate of useful information is enhanced, and the prediction performance of the wind speed time series can be improved. The training samples are reconstructed by the phase space reconstruction theory, and the connection weights of the network are trained by gradient descent method. And the hysteretic parameters are optimized by genetic algorithm. Simulation results show that the method can get better prediction performances than conventional neural network and ARMA model, and the prediction error can be reduced validly.关键词
神经网络/迟滞/风速时间序列/预测Key words
neural network/ hysteresis/ wind speed time series/ prediction分类
天文与地球科学引用本文复制引用
张欣,修春波,刘新婷,于婷婷..基于迟滞神经网络的风速时间序列预测[J].天津工业大学学报,2012,31(4):68-71,4.基金项目
国家自然科学基金资助项目(61078041) （61078041）
