文章基本信息

标题：Annual Rainfall Forecasting by Using Mamdani Fuzzy Inference System
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作者：Gholam Abbas Fallah-Ghalhary ; Mohammad Mousavi-Baygi ; Majid Habibi Nokhandan 等
期刊名称：Research Journal of Environmental Sciences
印刷版ISSN：1819-3412
电子版ISSN：2152-8238
出版年度：2009
卷号：3
期号：4
页码：400-413
DOI：10.3923/rjes.2009.400.413
出版社：Academic Journals Inc., USA
摘要：This research aims to study the relationship between climatic large-scale synoptic patterns and rainfall in Khorasan region. Fuzzy Inference System (FIS) was used in this study to predict rainfall in the period between December to May in the region. Soft computing is an innovative approach to construct computationally intelligent systems that are supposed to possess humanlike expertise within a specific domain, adapt themselves and learn to do better in changing environments and explain how they make decisions. Unlike conventional artificial intelligence techniques the guiding principle of soft computing is to exploit tolerance for imprecision, uncertainty, robustness, partial truth to achieve tractability and better rapport with reality. In this study, 33 years of rainfall data analyzed in khorasan region, situated at the northeastern part of Iran. This research attempted to train Fuzzy Inference System (FIS) based prediction models with 33 years of rainfall data. For performance evaluation, the model predicted outputs were compared with the actual rainfall data. Simulation results reveal that soft computing techniques are promising and efficient. The Root Mean Square Error by using Fuzzy Inference System model was obtained 52 millimeter.