The University of Basrah is investigating the hybridization of some time series in the agricultural sector in Iraq

The University of Basrah is investigating the hybridization of some time series in the agricultural sector in Iraq:
A master's thesis at the University of Basrah, College of Administration and Economics, Department of Statistics, by researcher Anwar Fawzi Muhammad.
The thesis aims to compare several single models: ARIMA, SVR, ARIMA-ANN, ARIMA-SVR, and hybrid ANN models, using some statistical measures for time series, to predict the gross domestic product of the agricultural sector in Iraq.

The thesis included observations of the recent significant development in the application of time series models in various fields, including agriculture, particularly the agricultural gross domestic product is of great importance to the lives of people, including self-sufficiency and non-reliance on imports. Predicting the agricultural GDP and obtaining accurate forecasts is important, as it reduces future risks for this important sector by providing the necessary means to improve the agricultural sector. The thesis recommended that statistical forecasts be used to make future decisions. A correct task depends on an accurate scientific method of prediction, and the most common methods in this framework are the ARIMA model, neural networks (ANN), and the support vector machine (SVR).