Hydrological Drought Forecasting, using Artificial Neural Network (ANN) and Predict Values of Hydrological Drought Condition Derived using River Water Level Data - Kumar Sharma, Rajesh; Rajput, Mayank; Sharma, Rahul (International Journal of Computer Sciences and Engineering, 2023)
This paper focuses on hydrological drought forecasting, using Artificial Neural Network (ANN) and predicts the values of hydrological drought condition derived using Narmada River Water level data of Hoshangabad (M.P). We have used the water level data as input data of ANN model for hydrological drought forecasting, and determine Standardized Water Level Index (SWLI). Artificial Neural networks operate on the principle of learning from a training set. There is a large variety of neural network models and learning procedures. Two classes of neural networks that are usually used for prediction applications are feed-forward networks and recurrent networks. They often train both of these networks using back-propagation algorithm.