论文信息 - DETECTOR: A knowledge-based system for injection molding diagnostics

DETECTOR: A knowledge-based system for injection molding diagnostics

A knowledge-based system (KBS) for diagnosis of multiple defects in injection molding is presented. The general scheme for knowledge representation based on fuzzy set theory has been shown useful in representing inexact and incomplete information for developing the KBS. An optimality criterion is created for selecting a simple and ‘best’ cover to explain the given problem. An efficient search algorithm for finding such cover is also discussed.

Jih-Forg Kao | Ioannis O. Pandelidis | I. Pandelidis | Jih-Forg Kao

[1] James A. Reggia,et al. Diagnostic Expert Systems Based on a Set Covering Model , 1983, Int. J. Man Mach. Stud..

[2] J. Shanteau,et al. Livestock judges: How much information can an expert use? , 1978 .

[3] Edward H. Shortliffe,et al. Chapter 3 – Consultation System , 1976 .

[4] Edward H. Shortliffe,et al. Computer-based medical consultations, MYCIN , 1976 .

[5] A. Kandel. Fuzzy Mathematical Techniques With Applications , 1986 .

[6] Michio Sugeno,et al. An introductory survey of fuzzy control , 1985, Inf. Sci..

[7] James A. Reggia,et al. Computer-Assisted Medical Decision Making , 1985, Computers and Medicine.

[8] R. R. Kadesch,et al. Subjective Inference with Multiple Evidence , 1986, Artif. Intell..

[9] Max Henrion,et al. Uncertainty in artificial intelligence: Is probability epistemologically and heuristically accurate? , 1987 .

[10] Ivan Bratko,et al. Prolog Programming for Artificial Intelligence , 1986 .

[11] J. Reggia,et al. An introduction to computer-assisted medical decision making. I. , 1985, M.D. computing : computers in medical practice.

[12] Lotfi A. Zadeh,et al. Fuzzy sets and information granularity , 1996 .