NDLI: Neuro-Fuzzy Decision Tree by Fuzzy ID3 Algorithm and Its Application to Anti-Dumping Early-Warning System

Content Provider	IEEE Xplore Digital Library
Author	Jianna Zhao Zhipeng Chang
Copyright Year	2006
Description	Author affiliation: Sch. of Bus. & Adm., North China Electr. Power Univ., Baoding (Jianna Zhao; Zhipeng Chang)
Abstract	Fuzzy decision trees (FDT) are one of the most popular choices for learning and reasoning from dataset. They have undergone a number of alterations to language and measurement uncertainties. However, they are poor in classification accuracy. In this paper, we proposed neuro-fuzzy decision tree. Neuro-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. In the forward cycle, we construct fuzzy decision trees using fuzzy ID3. In the feedback cycle, parameters of fuzzy decision trees have been adapted using stochastic gradient descent algorithm by traversing back from leaf to root nodes. In this paper, we proposed a new anti-dumping early-warning system. The early-warning system based on neuro-fuzzy decision tree modeling method is different from traditional modeling methods. 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
Starting Page	1300
Ending Page	1304
File Size	400084
Page Count	5
File Format	PDF
ISBN	1424405289
DOI	10.1109/ICIA.2006.305939
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-08-20
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Neuro-fuzzy decision tree Fuzzy ID3 Humans Stochastic processes Fuzzy sets Anti-Dumping Early-warning Backpropagation algorithms Decision trees Textile industry Neurofeedback Fuzzy systems Classification tree analysis Testing
Content Type	Text
Resource Type	Article

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