Title :
Recognizing knowledge imperfection in the risk management process
Author :
Jablonowski, Mark
Author_Institution :
Risk Manage. Dept., Windsor Locks, CT, USA
Abstract :
Risk managers choose from a variety of methods to minimize the effects of accidental loss upon their organizations. The choice depends upon the probability/loss characteristics of a given exposure, This specification is not exact, however, due to a dynamic and complex environment. As a result, the decision is usually made under conditions of knowledge imperfection. The imprecision inherent in the risk management process can be formalized using the concept of fuzziness
Keywords :
accidents; business data processing; fuzzy set theory; knowledge based systems; risk management; uncertainty handling; accidental loss; businesses; complex environment; expert systems; fuzziness concept; knowledge imperfection recognition; probability/loss characteristics; risk management process; risk managers; specification; uncertainty; Business; Decision making; Earthquakes; Expert systems; Fires; Law; Legal factors; Risk management; Standards organizations; Uncertainty;
Conference_Titel :
Uncertainty Modeling and Analysis, 1995, and Annual Conference of the North American Fuzzy Information Processing Society. Proceedings of ISUMA - NAFIPS '95., Third International Symposium on
Conference_Location :
College Park, MD
Print_ISBN :
0-8186-7126-2
DOI :
10.1109/ISUMA.1995.527659