Identifying Smart Strategies for Effective Agriculture Solution Using Data Mining Techniques. (13th April 2022)

• Record Type: Journal Article
• Authors: Suarez, Anthony Jesus Bustamante; Singh, Barjinder; Almukhtar, Firas Husham; Kler, Rajnish; Vyas, Sonali; Kaliyaperumal, Karthikeyan
• Other Names: Khan Rijwan Academic Editor.
• Is Part Of: Journal of food quality. Volume 2022(2022)
• Publication Date: 2022-04-13
• Subjects: Food industry and trade -- Quality control -- Periodicals; Food industry and trade -- Standards -- Periodicals; Food -- Periodicals; 664.07
• DOI: 10.1155/2022/6600049
• Languages: English
• ISSNs: 0146-9428

Abstract

Abstract : 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.