Abstract

With the gradual development of artificial intelligence (AI), the traditional production, marketing, and management methods for agricultural products have undergone dramatic changes, necessitating a greater optimization of these methods. Agricultural product operators have begun incorporating AI technology into product production, marketing, and distribution processes. This article examines the current state of agricultural product management and then investigates the integration of production, marketing, and distribution using artificial intelligence. In addition, given the limitations of conventional methods for classifying agricultural products, this article presents a classification model that combines factor analysis with an enhanced support vector machine (SVM) based on genetic algorithms (GAs). The results of the experiments indicate that the improved method is capable of distinguishing agricultural product quality categories rapidly and precisely, significantly improving the classification accuracy of agricultural product quality, and being broadly applicable to the evaluation of agricultural product quality.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.