Time series forecasting in the artificial intelligence milieu

Time Series Forecasting Using Computational Intelligence Methods

Abstract: Forecasting the future evolution of a system based only on past information comprises a central scientific problem. In this work we investigate the comparative performance of recurrent multi–layer perceptrons, trained through backpropagation through time and the differential evolution algorithm, to perform one–step–ahead predictions for the laser time series (Data set A) from the Sant...

A comparison of performance of several artificial intelligence methods for forecasting monthly discharge time series

Combining Artificial Intelligence with Non-linear Data Processing Techniques for Forecasting Exchange Rate Time Series

Combing back-propagation neural network (BPNN) and empirical mode decomposition (EMD) techniques, this study proposes EMD-BPNN model for forecasting. In the first stage, the original exchange rate series were first decomposed into a finite, and often small, number of intrinsic mode functions (IMFs). In the second stage, kernel predictors such as BPNN were constructed for forecasting. Compared w...

Artificial neural networks in time series forecasting: a comparative analysis

Artificial neural networks (ANN) have received a great deal of attention in many fields of engineering and science. Inspired by the study of brain architecture, ANN represent a class of nonlinear models capable of learning from data. ANN have been applied in many areas where statistical methods are traditionally employed. They have been used in pattern recognition, classification, prediction an...

AN EXTENDED FUZZY ARTIFICIAL NEURAL NETWORKS MODEL FOR TIME SERIES FORECASTING

Improving time series forecastingaccuracy is an important yet often difficult task.Both theoretical and empirical findings haveindicated that integration of several models is an effectiveway to improve predictive performance, especiallywhen the models in combination are quite different. In this paper,a model of the hybrid artificial neural networks andfuzzy model is proposed for time series for...