By Topic

Research on the Early Warning Model Based on the Fuzzy Rough Set and BP Neural Network

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Guorui Jiang ; Sch. of Econ. & Manage., Beijing Univ. of Technol., Beijing, China ; Liduan Ma

In this paper, a method of complement of fuzzy rough set and BP neural network was proposed, and an early warning model of electronic information products on Technical Barriers to Trade (TBT) was given by the method. The attribute reduction for indicators of early warning based on fuzzy rough set can not only enhance the veracity of attribute reduction, but also improve the accuracy of the training of BP neural network through reducing the input dimension of BP neural network at the same time. The new TBT early warning model of electronic information products was proved more feasible and effective.

Published in:

2010 2nd International Conference on E-business and Information System Security

Date of Conference:

22-23 May 2010