Title :
Qualitativeness does not imply fuzziness
Author :
Leitch, R.R. ; Shen, Q.
Author_Institution :
Dept. of Electr. & Electron. Eng., Heriot-Watt Univ., Edinburgh, UK
Abstract :
The motivations for qualitative modelling and fuzzy modelling are almost identical: to cope with the complexities in the modelling of real systems. However, their developments have been independent, distinct and complementary. The synthesis of these techniques has required a re-appraisal of exactly what model properties are used in these techniques. We argue that precision and uncertainty are distinct concepts. Qualitative modelling deals with abstract imprecise models whilst fuzzy modelling copes with uncertain imprecise or precise models, With this clarification we have developed a fuzzy qualitative simulation system, an outline of which is given in this paper. We believe that such combinations of fuzzy and qualitative methods are the natural development of Zadeh´s original proposal for intelligent reasoning about complex systems
Keywords :
common-sense reasoning; fuzzy logic; fuzzy set theory; inference mechanisms; knowledge representation; modelling; uncertainty handling; abstract imprecise models; fuzzy modelling; fuzzy qualitative simulation; intelligent reasoning; precision; qualitative modelling; uncertain models; uncertainty; Artificial intelligence; Automatic control; Control systems; Fuzzy reasoning; Fuzzy sets; Fuzzy systems; Humans; Proposals; Systems engineering and theory; Uncertainty;
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
DOI :
10.1109/FUZZY.1994.343641