Flood Forecasting using Adaptive Neuro-Fuzzy Inference System (ANFIS)

  IJETT-book-cover  International Journal of Engineering Trends and Technology (IJETT)          
© 2014 by IJETT Journal
Volume-12 Number-10
Year of Publication : 2014
Authors : Dushyant Patel , Dr. Falguni Parekh


Dushyant Patel , Dr. Falguni Parekh. "Flood Forecasting using Adaptive Neuro-Fuzzy Inference System (ANFIS) ", International Journal of Engineering Trends and Technology (IJETT), V12(10),510-514 June 2014. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group


The aim of the present study is to explore applicability of artificial intelligence techniques such as ANFIS (Adaptive Neuro-Fuzzy Inference System) in forecasting flood for the case study, Dharoi Dam on the Sabarmati river near village Dharoi in Kheralu Taluka of Mehsana District in Gujarat State, India. The proposed technique combines the learning ability of neural network with the transparent linguistic representation of fuzzy system. ANFIS models with various input structures and membership functions are constructed, trained and tested to evaluate the models. Statistical indices such as Root Mean Square Error (RMSE), Correlation Coefficient (R), Coefficient of Determination (R2) and Discrepancy Ratio (D) are used to evaluate performance of the ANFIS models in forecasting flood. This objective is accomplished by evaluating the model by comparing ANFIS model to Statistical method like Log Pearson type-III method to forecasting flood. This comparison shows that ANFIS model can accurately and reliably be used to forecast flood in this study.


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Adaptive Neuro-Fuzzy Inference System, Flood forecasting, Statistical method.