Fuzzy Methodology for Taxonomy and Knowledge Base Design  

作　　者：Paul P. Wang & Fuji Lai(Fuzzy Logic Research Laboratory, Department of Electrical Engineering Duke University, Box 90291, Durham, North Carolina 27708-0291)email: { [e-mail] & flai @acpub.duke.edu } . 

出　　处：《Journal of Systems Engineering and Electronics》1996年第2期1-23,共23页系统工程与电子技术（英文版）

摘　　要：This paper summarizes the research results dealing with washer and nut taxonomy and knowledge base design, making the use of fuzzy methodology. In particular, the theory of fuzzy membership functions, similarity matrices, and the operation of fuzzy inference play important roles.A realistic set of 25 washers and nuts are employed to conduct extensive experiments and simulations.The investigation includes a complete demonstration of engineering design. The results obtained from this feasibility study are very encouraging indeed because they represent the lower bound with respect to performance, namely correctrecognition rate, of what fuzzy methodology can do. This lower bound shows high recognition rate even with noisy input patterns, robustness in terms of noise tolerance, and simplicity in hardware implementation. Possible future works are suggested in the conclusion.This paper summarizes the research results dealing with washer and nut taxonomy and knowledge base design, making the use of fuzzy methodology. In particular, the theory of fuzzy membership functions, similarity matrices, and the operation of fuzzy inference play important roles.A realistic set of 25 washers and nuts are employed to conduct extensive experiments and simulations.The investigation includes a complete demonstration of engineering design. The results obtained from this feasibility study are very encouraging indeed because they represent the lower bound with respect to performance, namely correctrecognition rate, of what fuzzy methodology can do. This lower bound shows high recognition rate even with noisy input patterns, robustness in terms of noise tolerance, and simplicity in hardware implementation. Possible future works are suggested in the conclusion.

关 键 词：Feature extraction Pattern recognition Fuzzy set theory TAXONOMY Fuzzy similarity matrix Industrial washer and nut classification Knowledge base design Database transformation Cognitive science Industrial part identification 

分 类 号：TP182[自动化与计算机技术—控制理论与控制工程]