计算机应用研究Issue(9)：2630-2633,2638,5.DOI:10.3969/j.issn.1001-3695.2015.09.017
基于ARIMA与WASD N加权组合的时间序列预测
Time series forecasting based on weighted combination of ARIMA and WASDN
摘要
Abstract
In order to improve the forecasting accuracy and enhance the applicability of the time series forecasting approach, this paper proposed a novel weighted combination method,namely ARIMA-WASDN method.This method simultaneously exploited the ARIMA model and WASDN (short for the power-activation feed-forward neuronet equipped with the WASD algo-rithm)to model,test and forecast the time series.According to the results of testing,two models could be combined into one model in a weighted manner for time series forecasting.Numerical experiment results indicate that the ARIMA-WASDN method can improve the accuracy achieved via either of the models used separately,and the results further illustrate the effectiveness and superiority of the proposed ARIMA-WASDN method in terms of time series forecasting.关键词
差分自回归移动平均模型/权值与结构确定算法/幂激励前向神经网络/时间序列预测/加权组合Key words
ARIMA model/WASD algorithm/power-activation feed-forward neuronet/time series forecasting/weighted combination分类
信息技术与安全科学引用本文复制引用
张雨浓,劳稳超,丁玮翔,王英,叶成绪..基于ARIMA与WASD N加权组合的时间序列预测[J].计算机应用研究,2015,(9):2630-2633,2638,5.基金项目
国家社会科学基金资助项目（13BXW037）；自主系统与网络控制教育部重点实验室开放基金资助项目 （）
