Identifying Smart Strategies for Effective Agriculture Solution Using Data Mining Techniques - Anthony Jesus Bustamante Suarez; Barjinder Singh; Firas Husham Almukhtar; Rajnish Kler; Sonali Vyas; Karthikeyan Kaliyaperumal (Journal of Food Quality)
Agricultural producers and enterprises face a dizzying array of decisions every day, and the many factors that influence them are incredibly complex. Agricultural planning relies heavily on accurately calculating the yields of the various crops that will be used. If you want realistic and successful solutions, data mining is an essential component. Researchers in this study are looking for ways to evaluate agricultural data and extract valuable information from the results in order to increase agricultural output. Use of the CART and random forest algorithms is a data mining technique that may be used to various datasets. It is possible to recognise the effects of various climatic and other factors on agricultural output using the MATLAB software and data mining methods, and a potential strategy is highlighted.