Analysis and Research on the Marketing Strategy of Agricultural Products Based on Artificial Intelligence

被引:0
|
作者
Wang, Hongbing [1 ,2 ]
Gao, Jing [3 ]
Kang, Bohan [2 ]
Lyu, Peng [1 ]
Shi, Yuxian [1 ]
机构
[1] Jeonju Univ, Jeonju, Jeollabuk, South Korea
[2] Shijiazhuang Informat Engn Vocat Coll, Shijiazhuang 050000, Hebei, Peoples R China
[3] Hebei Transportat Investment Grp Corp, Shijiazhuang 050000, Hebei, Peoples R China
关键词
SUPPORT VECTOR REGRESSION; GENETIC ALGORITHM; MODEL; SELECTION;
D O I
10.1155/2022/7798640
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
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.
引用
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页数:7
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