Crops Production Predict Using Machine Learning on Perspective of Bangladesh

Abstract

Bangladesh is predominantly agricultural country and the agriculture sector is crucial to the country's economic development. To maintain long-term food security for humans, it is necessary to developing a productive, stable, and ecologically friendly agricultural system. Researchers in agriculture are working hard to develop techniques that will boost livestock and crop yields, improve farmland productivity and minimize the diseases and insect damage. They strive to increase overall food quality and construct more efficient equipment. This research work proposed a system for estimating the production of twelve distinct crops cultivated in Bangladesh's Cumilla and Chandpur districts. This system takes a few simple characteristics as input (district, sub district, crop name, and area) and predicts crop yield as output. Random Forest Regression and Decision Tree Regression are used in this study as advanced regression systems. People will be able to determine which crop will produce the maximum yield on their land by using this approach.