A Methodology for Crop Price Prediction Using Machine Learning

Every nation on the globe depends heavily on agriculture. Numerous issues with agriculture still need to be resolved, such as yield recommendations and crop price forecasting based on market value. This might boost farmers’ livelihoods and increase yield as well. Modern technologies of today have also been demonstrated to be capable of producing an automated advanced application for a diverse range of purposes. Machine learning models namely, decision tree and neuro-evolutionary algorithms are used in the proposed work to provide an improved crop productivity and pricing estimate. The paper provides a comprehensive analysis on the machine learning based techniques/algorithms used in the agricultural segment. The outcomes of the proposed system were demonstrated and illustrated how far it is efficient. As an extension to this work, an automated price recommendation system using genetic algorithm shall be designed in the future.