Applying Machine Learning to Semiconductor Manufacturing
IEEE Expert: Intelligent Systems and Their Applications
The Data-Mining Industry Coming of Age
IEEE Intelligent Systems
A complete fuzzy decision tree technique
Fuzzy Sets and Systems - Theme: Learning and modeling
A CBR-based fuzzy decision tree approach for database classification
Expert Systems with Applications: An International Journal
Fuzzy decision trees: issues and methods
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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Manufacturing organizations are striving to remain competitive in an era of increased competition and every-changing conditions. Manufacturing technology selection is a key factor in the growth of an organization and a fundamental challenge is effectively managing the computation of data to support future decision-making. Classification is a data mining technique used to predict group membership for data instances. Popular methods include decision trees and neural networks. This paper investigates a unique fuzzy reasoning method suited to engineering applications using fuzzy decision trees. The paper focuses on the inference stages of fuzzy decision trees to support decision-engineering tasks. The relaxation of crisp decision tree boundaries through fuzzy principles increases the importance of the degree of confidence exhibited by the inference mechanism. Industrial philosophies have a strong influence on decision practices and such strategic views must be considered. The paper is organized as follows: introduction to the research area, literature review, proposed inference mechanism and numerical example. The research is concluded and future work discussed.