All submissions of the EM system will be redirected to Online Manuscript Submission System. Authors are requested to submit articles directly to Online Manuscript Submission System of respective journal.

Abstract

City innovation capability evaluation method based on support vector machine

Author(s): Yong-li Zhang, Yan-wei Zhu

China will develop into an innovative country in 2020. It has become an important topic that study on evaluation method of innovation ability. But the science and technology innovation capacity determination is complex, there are many factors affecting the innovation ability, there are a non-linear relationship, uncertainty and ambiguity. Support vector machine is a statistical learning method based on small samples, using structural risk minimization principle, and it is good generalization ability. This paper uses support vector regression algorithm to evaluate the ability of innovation of science and technology, get the support vector machine regression model, Through the 2013 yearbook data analysis of the experimental results, this method is achieved very good results in evaluation of regional innovation capacity.


Share this       

Share this Page.

Table of Contents

Scimago Journal Rank

Flyer
izmir escort izmir escort bursa escort antalya escort izmir escort porno porno izle türk porno eskişehir escort bartın escort burdur escort havalandırma izmir escort bursa escort porno indir izle escort izmir