Application of Improved SVR Model in Ecological Economy Prediction

被引：1

作者：

Li, Yan ^{[1
]}

Long, Yuening ^{[2
]}

机构：

[1] Yunnan Univ, Sch Life Sci, Kunming 650500, Peoples R China

[2] Yunnan Minzu Univ, Sch Law, Kunming 650500, Peoples R China

来源：

PROCEEDINGS 2015 SIXTH INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS DESIGN AND ENGINEERING APPLICATIONS ISDEA 2015 | 2015年

关键词：

support vector regression; ecological economy prediction; intelligent algorithm; SUPPORT VECTOR MACHINES; CLASSIFICATION; PARAMETER;

D O I：

10.1109/ISDEA.2015.48

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Principle of support vector regression method is investigated. Genetic algorithm is adopted to search the optimal SVR parameters to improve the generalization performance of SVR. Then an improved SVR method based on intelligent computing is put forward. At last, the proposed method is used in the prediction of ecological tourism economy. Different kernel functions are used for training data, and the performance of the prediction is compared. The predictive effect of RBF kernel function is significantly better than that of the polynomial kernel function. The proposed method can provide important reference for the development of ecological tourism economy.

引用

页码：155 / 158

页数：4

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