Assessment of Environmental Effect of Chinese Foreign Trade Based on Rough Sets and SVM

Author

Zhao, Xu ; Wu Zhuozheng ; Xu Zhao

Author_Institution

Sch. of Bus. & Adm., North China Electr. Power Univ.

fYear

2008

fDate

27-28 Dec. 2008

Firstpage

256

Lastpage

259

Abstract

A hybrid intelligent system is applied to assess the environment effect of Chinese foreign trade, combining rough set approach and support vector machines (SVM). We can get reduced information table with no information loss by rough sets approach. And then, this reduced information is used to develop classification rules and train SVM. The effectiveness of our methodology was verified by experiments comparing BP neural networks with our approach.

Keywords

international trade; macroeconomics; pattern classification; rough set theory; support vector machines; BP neural network; Chinese foreign trade environmental effect assessment; classification rule; hybrid intelligent system; information table; rough set theory; support vector machine training; Economic forecasting; Environmental economics; Hybrid intelligent systems; Information systems; International trade; Neural networks; Power system modeling; Rough sets; Support vector machine classification; Support vector machines; Rough Sets; SVM; environment effect; foreign trade;

fLanguage

English

Publisher

ieee

Conference_Titel

Modelling, Simulation and Optimization, 2008. WMSO '08. International Workshop on

Conference_Location

Hong Kong

Print_ISBN

978-0-7695-3484-8

Type

conf

DOI

10.1109/WMSO.2008.82

Filename

4757001