The Method and Application of Time Series Prediction Based Wavelet Neural Network

摘要：

This paper presents a research on modeling and prediction with wavelet neural network in the nonlinear time series of gas emitted. Because accurately predicting the amount of gas emitted from the mine is a very important matter for safety, this paper proposes a new algorithm of wavelet neural network model for time series gas emission prediction. The nervous cells function is the basis of nonlinear wavelets. A wavelet network composed by the wavelet basis function is computed by an expansion and contraction factor and a translation factor to reach the global best approximation effect. Which wavelet basis function has the features of extraction capabilities, self-learning neural network and wavelet transform of the localized nature. The intrinsic defects of artificial BP neural network, e.g., its slow learning speed, difficulty to determine rationally the network structure and existence of partial minimum points, are solved. The simulation results obtained show that the new prediction system has faster conver ence and more accurate prediction.

关键词： Time series predicting Wavelet neural network Gas emission

作者: Yumin Pan Quanzhu Zhang Pengqian Xue

作者单位: North China Institute of Science & Technology, Yanjiao, East Beijing 101601, China

会议类型: 国际会议

会议名称: 2011 International Conference on Mechatronics and Materials Processing(2011年机电一体化与材料加工国际会议 ICMMP)

会议地点: 广州

会议语种:英文

页码: 2312-2317

在线出版日期: 2011-11-18（万方平台首次上网日期，不代表论文的发表时间）