Time series forecasting with a nonlinear model and the scatter search meta-heuristic

DOI10.1016/j.ins.2008.03.024zbMath1142.62069OpenAlexW2007789460MaRDI QIDQ942313

Carlos Gomes da Silva

Publication date: 5 September 2008

Published in: Information Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ins.2008.03.024

zbMATH Keywords

forecastnonlinear modelsmeta-heuristicsARMAscatter search

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10)

Related Items

Towards the evaluation of time series protection methods, Generalized exponential autoregressive models for nonlinear time series: stationarity, estimation and applications, A morphological-rank-linear evolutionary method for stock market prediction, Recentness biased learning for time series forecasting, A hybrid algorithm to optimize RBF network architecture and parameters for nonlinear time series prediction

Uses Software

• Scatter Search

Cites Work

• Time series forecasting using a hybrid ARIMA and neural network model
• Hybridization of intelligent techniques and ARIMA models for time series prediction
• A simple method of forecasting based on fuzzy time series
• Scatter search. Methodology and implementation in C. With CD-ROM.
• Time series forecasting by combining RBF networks, certainty factors, and the Box-Jenkins model
• Non-linear financial time series forecasting - Application to the Bel 20 stock market index
• Time-series forecasting using GA-tuned radial basis functions