DocumentCode
3773974
Title
Agricultural Economic Evaluation Based on Improved Support Vector Regression
Author
Min Huang
Author_Institution
Qinhai Univ., China
fYear
2015
fDate
6/1/2015 12:00:00 AM
Firstpage
118
Lastpage
121
Abstract
The essence of agricultural project bid is a high-dimensional nonlinear space mathematical optimization problem. In order to improve the generalization performance of SVR algorithm, intelligent algorithm is used to train the SVR parameters, which can make the parameters of SVR optimal. The improved support vector regression evaluation model is applied to the bidding area of agricultural project. The success of some project in some agricultural company proves the reliability and enforceability of the model. The improved model reduces the influence of human factors to improve the objectivity and impartiality of evaluation results.
Keywords
"Support vector machines","Companies","Kernel","Optimization","Genetic algorithms","Economics","Training"
Publisher
ieee
Conference_Titel
Intelligent Computation Technology and Automation (ICICTA), 2015 8th International Conference on
Type
conf
DOI
10.1109/ICICTA.2015.38
Filename
7473250
Link To Document