Showing papers on "Fuzzy associative matrix published in 1977"
TL;DR: In this article, a fuzzy logic is used to synthesize linguistic control protocol of a skilled operator for industrial plants, which has been applied to pilot scale plants as well as in practical situations.
Abstract: This paper describes an application of fuzzy logic in designing controllers for industrial plants. A fuzzy logic is used to synthesize linguistic control protocol of a skilled operator. The method has been applied to pilot scale plants as well as in practical situations. The merits of this method and its usefulness to control engineering are discussed. An avenue for further work in this area is described where the need is to go beyond a purely descriptive approach, and means for implementing a prescriptive or a self-organizing system are explored.
2,011 citations
01 Jul 1977-International Journal of Human-computer Studies \/ International Journal of Man-machine Studies
TL;DR: This paper presents a model for solving multi-objective decision problems when the objectives are of varying degrees of importance by assigning to each objective a power indicative of its importance and then raising each fuzzy set to its appropriate power.
Abstract: One of the most useful aspects of fuzzy set theory is its ability to represent multio-bjective decision problems involving vague or fuzzy objectives. This paper presents a model for solving multi-objective decision problems when the objectives are of varying degrees of importance. This is done by assigning to each objective a power indicative of its importance and then raising each fuzzy set to its appropriate power. These powers are obtained by getting the eigenvector of the maximum eigenvalue of a matrix of paired comparisons of the objectives.
452 citations
245 citations
TL;DR: In this paper, some sufficient conditions for convergence under “max(min)” products of the powers of a square fuzzy matrix and of a fuzzy state process are established.
229 citations
TL;DR: Using fuzzy measures and fuzzy integrals, a mathematical model of learning is presented which is able to learn through fuzzy information and is compared with an ordinary Bayesian learning model.
Abstract: Using fuzzy measures and fuzzy integrals, the paper presents a mathematical model of learning which is able to learn through fuzzy information. The characteristics of the model are studied theoretically and in numerical examples, where the model is compared with an ordinary Bayesian learning model. The problem of seeking an extremum of multimodel objective function is given as an example.
84 citations
TL;DR: The principal advantages of this technique are the new concept of direct simplification via essential fuzzy prime implicants (without generation of all of the fuzzy primeimplicants), and the fact that the algorithm is the first one to be suitable for efficient computer implementation.
Abstract: This paper is concerned with the study of simplification of fuzzy switching functions. A novel algorithm for generating all fuzzy prime implicants is introduced, followed by a new method of simplification of fuzzy switching functions. This algorithm is then reduced to a simple algorithm that produces only those fuzzy prime implicants that are essential. There areonly two other valid techniques for the minimization of fuzzy switching functions in the literature,(1,2) and those methods are not very suitable for computerized application. Thus, the principal advantages of this technique are the new concept of direct simplification via essential fuzzy prime implicants (without generation of all of the fuzzy prime implicants), and the fact that the algorithm is the first one to be suitable for efficient computer implementation.
12 citations