Rainfall prediction in the northeast region of Thailand using Modular Fuzzy Inference System
Kajornrit, J., Wong, K.W. and Fung, C.C. (2012) Rainfall prediction in the northeast region of Thailand using Modular Fuzzy Inference System. In: IEEE International Conference on Fuzzy Systems, FUZZ 2012, 10 - 15 June, Brisbane, Australia pp. 1-6.
*Subscription may be required
In water management systems, accurate rainfall forecasting is indispensable for operation and management of reservoir, and flooding prevention because it can provide an extension of lead-time of the flow forecasting. In general, time series prediction has been widely applied to predict rainfall data. The conventional time series prediction models or artificial neural networks can be used to perform this task. However, such models are difficult to interpret by human analyst. From a hydrologist's point of view, the accuracy of the prediction and understanding the prediction model are equally important. This study proposes the use of a Modular Fuzzy Inference System (Mod FIS) to predict monthly rainfall data in the northeast region of Thailand. The experimental results show that the proposed model can be a good alternative method to provide both accurate results and human-understandable prediction mechanism.
|Publication Type:||Conference Paper|
|Murdoch Affiliation:||School of Information Technology|
|Copyright:||© 2012 IEEE|
|Item Control Page|
Downloads per month over past year