DocumentCode :
2272768
Title :
Learning from examples for the construction of fuzzy evaluations
Author :
Posthoff, Christian ; Schlosser, Michael
Author_Institution :
Dept. of Comput. Eng., Chemnitz Univ. of Technol., Germany
fYear :
1994
fDate :
26-29 Jun 1994
Firstpage :
368
Abstract :
Many concepts of knowledge-based problem-solving are incorporated into one system which has been based on set-theoretic concepts. This results in a methodology and in a comprehensive set of tools applicable in many fields. The transition between fuzzy and non-fuzzy parts of the problem domain can be realized very flexibly, supplying a high smartness and high performance model. The paper has the intention to show how to unify many problem-solving methods on the basis of set theoretic concepts and how to handle precise and fuzzy notions concepts as flexible as possible
Keywords :
Boolean functions; fuzzy logic; fuzzy set theory; knowledge based systems; learning by example; problem solving; Boolean functions; fuzzy evaluations; fuzzy set theory; knowledge-based problem-solving; learning from examples; uncertainty handling; Artificial intelligence; Chemical elements; Chemical technology; Computer science; Decision trees; Equations; Fuzzy sets; Knowledge based systems; Problem-solving; Prototypes;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems, 1994. IEEE World Congress on Computational Intelligence., Proceedings of the Third IEEE Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-1896-X
Type :
conf
DOI :
10.1109/FUZZY.1994.343670
Filename :
343670
Link To Document :
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