Improvement of time forecasting models using a novel hybridization of bootstrap and double bootstrap artificial neural networks

• Main Authors: Zainuddin, Nurul Hila, Lola, Muhamad Safiih, Djauhari, Maman Abdurachman, Yusof, Fadhilah, Ramlee, Mohd. Noor Afiq, Deraman, Aziz, Ibrahim, Yahaya, Abdullah, Mohd. Tajuddin
• Format: Article
• Published: Elsevier Ltd 2019
• Subjects: Q Science (General)
• Online Access: http://eprints.utm.my/id/eprint/89501/; http://dx.doi.org/10.1016/j.asoc.2019.105676
• Institution: Universiti Teknologi Malaysia

Hybrid models such as the Artificial Neural Network-Autoregressive Integrated Moving Average (ANN–ARIMA) model are widely used in forecasting. However, inaccuracies and inefficiency remain in evidence. To yield the ANN–ARIMA with a higher degree of accuracy, efficiency and precision, the bootstrap a...