Time Series Prediction Using Hybrid ARIMA-ANN Models for Sugarcane

Recently Hybrid model approach has led to a tremendous surge in many domains of science and engineering. In this study, we present the advantage ANN improve time series forecasting precision. The Autoregressive Integrated Moving Average (ARIMA) Artificial Neural Network (ANN) models are used separately recognize linear nonlinear components data set respectively. manner, proposed tactically utilizes unique strengths ARIMA accuracy. Our hybrid method is tested on two Yamunanagar Panipat sugarcane Haryana. Results clearly indicate that ARIMA-ANN was better perform than with smaller values RMSE MAPE for both districts.