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• W1993933105 abstract "Rainfall prediction has become an integral part of the hydrological model. This paper presents the method of annual rainfall forecasting using wavelet transform and neuro-fuzzy approach based on the past history. The historical data have been decomposed into wavelet domain constitutive sub-series. The behaviour of the wavelet domain constitutive series has been studied based on the statistical analysis. Forecasting performance of the wavelet-coupled model has been compared with classical neuro-fuzzy, neural network and multiple linear regression models. The benchmark result shows that wavelet coupled model produces significantly better results in comparison with the neuro-fuzzy, neural network and regression models." @default.
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• W1993933105 date "2013-01-01" @default.
• W1993933105 modified "2023-09-27" @default.
• W1993933105 title "Annual Rainfall Prediction Using Neuro-Fuzzy and Wavelet Approach" @default.
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• W1993933105 doi "https://doi.org/10.5958/j.1945-919x.4.1a.002" @default.
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