Integration of Wavelet Transform with ANN and WNN for Time Series Forecasting: an Application to Indian Monsoon Rainfall

Abstract

Indian agricultural activity relies on monsoon rainfall; hence, its forecasting is indispensable for proper planning. Artificial neural network (ANN) is one of the popular approaches for rainfall forecasting. Recent research activity demonstrates that consolidating diverse model/techniques improves the exactness of forecasting when contrasted with the individual models. Therefore, the present study proposed a hybrid forecasting framework for rainfall forecasting combining wavelet transform, ANN and wavelet neural network (WNN). As a case study, Indian monsoon rainfall time series data have been considered to assess the forecasting performance of the proposed forecasting framework. The proposed approach has been compared with ANN and WNN. Observational outcomes uncover that the forecasting accuracy of the proposed strategy is superior to ANN and WNN.