In the present work, we consider the general problem of knowledge acquisition under uncertainty. A commonly used method is to learn by examples. We observe how the expert solves specific cases and from this infer some rules by which the decision was made. Unique to this work is the fuzzy set representation of the conditions or attributes upon which the decision make may base his fuzzy set decision. From our examples, we infer certain and possible rules containing fuzzy terms. It should be stressed that the procedure determines how closely the expert follows the conditions under consideration in making his decision. We offer two examples pertaining to the possible decision to close a customer service center of a public utility company. In th...
Decision making where goals or constraints are not sharply defined boundaries and fuzzy using dynami...
Intelligent control is a very successful way to transform the expert's knowledge of the type 'if the...
In this Chapter, the steps necessary to develop a fuzzy expert system (FES) from the initial model d...
Knowledge acquisition under uncertainty is examined. Theories proposed in deKorvin's paper 'Extracti...
Despite the advancements in the computer industry in the past 30 years, there is still one major def...
Although computers have come a long way since their invention, they are basically able to handle onl...
This dissertation reports on an effort to design, construct, test, and adjust an expert system for m...
Problems of implementing rule-based expert systems using fuzzy sets are considered. A fuzzy logic so...
A fuzzy set is a mathematical model of a collection of elements (objects) with fuzzy boundaries, whi...
Abstract: Looking at modern theories in management science and business administration, one recogniz...
The following article describes an approach covering the variety of opinions and uncertainties of es...
Fuzzy knowledge, that for which the terms of reference are not crisp but overlapped, seems to charac...
More and more companies today discover the advantages of using knowledge bases for their processes a...
Authors analyses questions of the subjective uncertainty and inexactness situations in the moment o...
Abstract- Decision making is an important aspect of any business entity. In this paper, a new lingui...
Decision making where goals or constraints are not sharply defined boundaries and fuzzy using dynami...
Intelligent control is a very successful way to transform the expert's knowledge of the type 'if the...
In this Chapter, the steps necessary to develop a fuzzy expert system (FES) from the initial model d...
Knowledge acquisition under uncertainty is examined. Theories proposed in deKorvin's paper 'Extracti...
Despite the advancements in the computer industry in the past 30 years, there is still one major def...
Although computers have come a long way since their invention, they are basically able to handle onl...
This dissertation reports on an effort to design, construct, test, and adjust an expert system for m...
Problems of implementing rule-based expert systems using fuzzy sets are considered. A fuzzy logic so...
A fuzzy set is a mathematical model of a collection of elements (objects) with fuzzy boundaries, whi...
Abstract: Looking at modern theories in management science and business administration, one recogniz...
The following article describes an approach covering the variety of opinions and uncertainties of es...
Fuzzy knowledge, that for which the terms of reference are not crisp but overlapped, seems to charac...
More and more companies today discover the advantages of using knowledge bases for their processes a...
Authors analyses questions of the subjective uncertainty and inexactness situations in the moment o...
Abstract- Decision making is an important aspect of any business entity. In this paper, a new lingui...
Decision making where goals or constraints are not sharply defined boundaries and fuzzy using dynami...
Intelligent control is a very successful way to transform the expert's knowledge of the type 'if the...
In this Chapter, the steps necessary to develop a fuzzy expert system (FES) from the initial model d...