Author(s): Radha M, Induja I and Kokilavani S

Abstract: Drought has a significant influence on both in the environment and in the area of agriculture, particularly farming. In this scenario, the Adaptive Neuro-Fuzzy Inference System (ANFIS), one of the hybrid artificial neural networks, is primarily used in this study to anticipate drought. The Coimbatore district's monthly precipitation values for the previous 39 years are used in this study. First, as the Coimbatore district primarily depends on the North-East Monsoon, SPI values are estimated at a 3-month scale using monthly precipitation values. Second, several ANFIS forecasting models are built employing the North-East Monsoon season's mean precipitation value as inputs. Additionally, Root Mean Sum of Error (RMS, Mean Absoulte Error (MAE) and coefficient of determination value (R²) were used to combine the results of the projected ANFIS model with the observed values. The best-fitting model was defined as having low RMSE, low MAE, and high R².

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