Prediction Method of Time Series Data Stream Based on Wavelet Transform and Least Squares Support Vector Machine

Time series data stream is widely concerned in industry engineering, finance, economy, traffic and many other fields, and data stream prediction is the important work. An efficient method for prediction of time series data stream using wavelet transform and least squares support vector machine (LS-SVM) is presented, which can provide high accuracy and cost less time. Sliding window model is used to follow the data changing, incremental algorithms for LS-SVM is used to save time. Simulation experiment using real power load dataset show the effectiveness of proposed method.