Support vector machine applied in the agriculture of Fanjing Mountain Areas

2nd International Symposium on Resource Exploration and Environmental Science

生态环境科学

Yuan, Lina^1 ; Chen, Huajun^1 ; Gong, Jing^1

College of Data Science, Tongren University, Tongren, China^1

关键词: Complete theory;    Domestic research;    Generalization performance;    Guizhou Province;    Hot topics;    Shape classification;    Training time;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/170/3/032049/pdf
DOI  :  10.1088/1755-1315/170/3/032049

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

The method of Support Vector Machine (SVM) in Machine Learning (ML) has the advantages of complete theory, strong adaptability, global optimization, short training time and good generalization performance, which has become a hot topic in international and domestic research. Therefore, it is of great meaning to apply SVM to the modernization and intellectualization agriculture of Fanjing Mountain Areas of Tongren city, Guizhou province. This article introduces the basic situation of Fanjing Mountain Areas's agriculture in Section I. Section II and III expounds the method of kernel and four multi-class SVMs respectively. A practical application case about the shape classification problem of "clenched fist" in SVM is done in Section IV, and finally Section V concludes the full text.