tailieunhanh - Forecasting of nitrogen content in the soil by hybrid time series model

There are several linear time-series forecasting models available in literature. One of the important and widely used technique for analysis of univariate time-series data is Box Jenkins’ Autoregressive integrated moving average (ARIMA) methodology (Box et al., 2007). Sometimes addition of the other exogenous variables increases the prediction accuracy of ARIMA model (ARIMAX). For this aspect we applied different p and q order ARIMAX model for five nutrient combinations of nitrogen content which is further developed by including organic carbons an input (exogenous) variable. Among the linear models the ARIMAX model performed better as compare to ARIMA model. But the performance of machine intelligence techniques like Hybrid of linear and nonlinear model is better as compared to linear time series models. | Forecasting of nitrogen content in the soil by hybrid time series model

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