Model identification of ARIMA family using genetic algorithms

By Chorng-Shyong Ong, Jih-Jeng Huang, Gwo-Hshiung Tzeng. 2005

129 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Economics and Econometrics, Management Science and Operations Research

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Abdelhamid Bouchachia

In Economics and Econometrics

1. Suhartono

In Management Science and Operations Research

1. Abdelhamid Bouchachia

Citations in the corpus

• Time Series Forecasting by using Seasonal Autoregressive Integrated Moving Average: Subset, Multiplicative or Additive Model (2011, background): “Ong et al. (2005) stated that although many previous papers have concentrated on model estimation, model identification is actually the most crucial stage in building ARIMA models, because false model identification will cause the wrong stage of model estimation and increase the cost of…”
• Hybridization of intelligent techniques and ARIMA models for time series prediction (2008, methodology): “Therefore, different approaches based on intelligent paradigms, such as neural networks, genetic algorithms or fuzzy system have been proposed to improve the accuracy of order selection of ARIMA models [63,74,25,20,39,42,41,31,13,8,14].”