Rainfall intensity forecast using ensemble artificial neural network and data fusion for tropical climate

Noor Zuraidin Mohd Safar*, David Ndzi, Hairulnizam Mahdin, Ku Muhammad Naim Ku Khalif

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper proposes an ensemble method based on neural network architecture and stacking generalization. The objective is to develop a novel ensemble of Artificial Neural Network models with back propagation network and dynamic Recurrent Neural Network to improve prediction accuracy. Historical meteorological parameters and rainfall intensity have been used for predicting the rainfall intensity forecast. Hourly predicted rainfall intensity forecast are compared and analyzed for all models. The result shows that for 1 h of prediction, the neural network ensemble forecast model returns 94% of precision value. The study achieves that the ensemble neural network model shows significant improvement in prediction performance as compared to the individual neural network model.

Original languageEnglish
Title of host publicationRecent Advances on Soft Computing and Data Mining - Proceedings of the 4th International Conference on Soft Computing and Data Mining, SCDM 2020
EditorsRozaida Ghazali, Nazri Mohd Nawi, Mustafa Mat Deris, Jemal H. Abawajy
PublisherSpringer
Pages241-250
Number of pages10
ISBN (Electronic)9783030360566
ISBN (Print)9783030360559
DOIs
Publication statusE-pub ahead of print - 5 Dec 2019
Event4th International Conference on Soft Computing and Data Mining, SCDM 2020 - Melaka, Malaysia
Duration: 22 Jan 202023 Jan 2020

Publication series

NameAdvances in Intelligent Systems and Computing
Volume978 AISC
ISSN (Print)2194-5357
ISSN (Electronic)2194-5365

Conference

Conference4th International Conference on Soft Computing and Data Mining, SCDM 2020
CountryMalaysia
CityMelaka
Period22/01/2023/01/20

Keywords

  • Artificial Neural Network
  • Ensemble learning
  • Expert system
  • Rainfall forecasting
  • Recurrent neural network
  • Tropical climate

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  • Cite this

    Mohd Safar, N. Z., Ndzi, D., Mahdin, H., & Khalif, K. M. N. K. (2019). Rainfall intensity forecast using ensemble artificial neural network and data fusion for tropical climate. In R. Ghazali, N. M. Nawi, M. M. Deris, & J. H. Abawajy (Eds.), Recent Advances on Soft Computing and Data Mining - Proceedings of the 4th International Conference on Soft Computing and Data Mining, SCDM 2020 (pp. 241-250). (Advances in Intelligent Systems and Computing; Vol. 978 AISC). Springer. https://doi.org/10.1007/978-3-030-36056-6_24