摘要
太阳黑子是表征太阳活动的重要现象,影响地球、人体乃至生命环境。针对影响太阳黑子的因子难以确定的问题,引入小波包和混沌相空间重构子序列揭示太阳黑子时间序列的动力学及物理规律。该方法采用小波包分解原始时间序列,用混沌相空间重构恢复影响因子,并采用小波神经网络预测子序列,再经小波包重构获得太阳黑子的最终预测结果。其中小波神经网络采用自行开发的工具箱,其具有方便、收敛速度快、数据吞吐量大、预测精度高以及实用性强等特点,对推广小波神经网络应用具有重要作用,并为太阳黑子数的预测提供了一条新途径。
Sunspot is an important phenomenon of the solar activity, and it is influencing the earth, human beings and the life environment. Because it is hard to identify the factors impacting the sunspots,we introduced the wavelet packet and chaos phase space reconstruction the subsequence,to find out the dynamics and physical laws of the sunspots time series. The method decomposes the original time series by wavelet packet, restructures and recovers the impact factors, predicts the subsequence by wavelet neural network toolbox and gets the final prediction result o/the sunspots by wave- let packet restructure. The wavelet neural network is developed by myself, which is convenient with fast convergence speed and great data-processing capacity and is accurate in prediction with strong practicality. The method plays an im- portant role to the promotion of using wavelet neural network, which provides a new way to predict the number of sun- spots.
出处
《计算机科学》
CSCD
北大核心
2013年第6期260-264,267,共6页
Computer Science
基金
国家安全生产监督管理总局安全生产科技发展指导性计划项目(06-472)
河北省教育厅科学技术研究项目(Z2006439)资助
关键词
太阳黑子
小波神经网络
工具箱
小波包
混沌
预测
Sunspots, Wavelet neural network, Toolbox, Wavelet packet, Chaotic, Prediction
