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Anti-Dumping Early-Warning System Based on Neuro-FDT

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2 Author(s)
Jian-na Zhao ; North China Electric Power University, China ; Zhi-peng Chang

In this paper, a new anti-dumping early-warning system for the export of China's textile products is presented. The early-warning system based on neuro-fuzzy decision tree modeling method is different from traditional modeling methods. Fuzzy decision trees are powerful, top-down, hierarchical search methodology to extract human interpretable classification rules. However, they are poor in classification accuracy. Neural networks-fuzzy decision tree (a fuzzy decision tree structure with neural like parameter adaptation strategy) improves FDT's classification accuracy and extracts more accuracy human interpretable classification rules. The other new attempt is the setting of early-warning intervals. The result of the positive research indicated that this system is very valid for anti-dumping prediction and it will have a good application prospect in this area

Published in:

Sixth International Conference on Intelligent Systems Design and Applications  (Volume:3 )

Date of Conference:

16-18 Oct. 2006