Development of AI-ML Based Models for Predicting Prices of Agri-Horticultural Commodities

Forestry is instrumental in maintaining security and stabilizing the economy. Over the last few years, the application of intelligence technologies like machine learning (ML) and artificial intelligence (AI) has grown in immense value in agriculture, especially to precisely predict the price of agricultural produce. It is of vital significance to farmers, traders, and the authorities, as price forecasts enable them to make better choices. This study deals with the usability of AI and ML methodologies in overcoming the problems of current agricultural price forecasting. These complex models are based on past records, along with several economic and environmental indicators, to forecast prices with a high level of precision. This helps farmers take good-informed decisions for growing crops, thus maximizing yields, minimizing losses, and adopting more efficient market policies. Furthermore, the forecasting ability of such models can dampen the effects of abrupt price shocks, leading to increased market stability and enhanced food availability. The results of this research will give useful insights to formulate sane policies and establish contribution of AI and ML in predicting agricultural prices.