Analysis and Comparison of Fuzzy Logic and Neural Network Based Study for Rainfall Predictions and Hydrological Modelling: A Case Study of Ahmedabad

Abstract

AbstractRainfall based forecasting, analysis and hydrological modelling form an integral part of the study of hydrology. Now a day’s many modern methods have been used for rainfall predictions. One of such tools which have been developed in recent times to promote the study of hydrological modelling and rainfall forecasting is by using fuzzy logic and ANN. The present study has been done out to analyze and compare the fuzzy logic and ANN based analysis for the rainfall predictions. Study also aims to demonstrate the use of hydrological modelling and the use of soft computing techniques for various hydrological purposes. Models developed using fuzzy logic and artificial neural network have been compared analysed and describes. Result shows that Artificial Neural Network gives suitable results over the Fuzzy Logic based model for the present study area and data taken. Analysis of the rainfall predictions and hydrological modelling for the study area has been done for fuzzy logic and the same study has been done through artificial neural network as well. The study shows that the use of Fuzzy and ANN is also suitable in Rainfall-Runoff Modelling as well. The efficiency of the model developed by Fuzzy Logic has been reflected up to 85 to 92% where is the efficiency of the model developed by artificial neural network has been reflected as 94 to 96%. Few models have been generated to compare and calibrate the analysis done on the study area.KeywordsRainfallHydrological modellingFuzzy logicANNRunoffModelling