Title :
Agricultural Economic Evaluation Based on Improved Support Vector Regression
Author_Institution :
Qinhai Univ., China
fDate :
6/1/2015 12:00:00 AM
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"
Conference_Titel :
Intelligent Computation Technology and Automation (ICICTA), 2015 8th International Conference on
DOI :
10.1109/ICICTA.2015.38