Conference paper
Rainfall prediction in the northeast region of Thailand using Cooperative Neuro-Fuzzy Technique
8th International Conference on Computing and Information Technology (Pattaya City, Thailand, 09/05/2012–10/05/2012)
2012
Abstract
Accurate rainfall forecasting is a crucial task for reservoir operation and flood prevention because it can provide an extension of lead-time for flow forecasting. This study proposes two rainfall time series prediction models, the Single Fuzzy Inference System and the Modular Fuzzy Inference System, which use the concept of cooperative neuro-fuzzy technique. This case study is located in the northeast region of Thailand and the pro-posed models are evaluated by four monthly rainfall time series data. The experimental results showed that the proposed models could be a good alternative method to provide both accurate results and human-understandable prediction mechanism. Furthermore, this study found that when the number of training data was small, the proposed model provided better prediction accuracy than artificial neural networks.
Details
- Title
- Rainfall prediction in the northeast region of Thailand using Cooperative Neuro-Fuzzy Technique
- Authors/Creators
- J. Kajornrit (Author/Creator)K.W. Wong (Author/Creator)C.C. Fung (Author/Creator)
- Conference
- 8th International Conference on Computing and Information Technology (Pattaya City, Thailand, 09/05/2012–10/05/2012)
- Identifiers
- 991005545558007891
- Murdoch Affiliation
- School of Information Technology
- Language
- English
- Resource Type
- Conference paper
- Note
- In: Proceedings of IC2IT 2012 The 8th International Conference on Computing and Information Technology, 2012, 9-10 May, Pattaya City, Thailand, pp 24 - 29
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