Title :
Anti-Dumping Early-Warning System Based on Neuro-FDT
Author :
Zhao, Jian-Na ; Chang, Zhi-peng
Author_Institution :
Sch. of Bus. & Adm., North China Electr. Power Univ., Baoding
Abstract :
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
Keywords :
decision trees; fuzzy neural nets; pattern classification; textile industry; antidumping early-warning system; classification rule extraction; neural networks; neuro-fuzzy decision tree modeling; search methodology; textile products; Backpropagation algorithms; Classification tree analysis; Decision trees; Electronic mail; Fuzzy sets; Humans; Inspection; Power system modeling; Testing; Textile industry;
Conference_Titel :
Intelligent Systems Design and Applications, 2006. ISDA '06. Sixth International Conference on
Conference_Location :
Jinan
Print_ISBN :
0-7695-2528-8
DOI :
10.1109/ISDA.2006.13