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.
CITATION STYLE
Wang, H., Gaojing, Kang, B., Peng, L., & Shi, Y. (2022). Analysis and Research on the Marketing Strategy of Agricultural Products Based on Artificial Intelligence. Mathematical Problems in Engineering, 2022. https://doi.org/10.1155/2022/7798640
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