Showing papers on "Membership function published in 1975"

Description and optimization of fuzzy systems

Abstract: The concept of fuzzy sets is presented as a new tool for the formulation and solution of systems and decision problems which contain fuzzy components or fuzzy relationships. After a brief description of the basic theory of fuzzy sets, implications to systems theory and decision making are indicated. Fuzzy set theory is then applied to fuzzy linear programming problems and it is shown how fuzzy linear programming problems can be solved without increasing the computational effort. Some critical remarks concerning the presently existing axioms and necessary future research efforts conclude this introductionary paper.

Decision making with fuzzy sets

Abstract: When goals and constraints are stated imprecisely, decision problems grow in importance, particularly in the investigation of complex and social systems. In this paper the methodology of Zadeh's fuzzy set theory is summarized and applied to fuzzy decision making.

On risk and decision making in a fuzzy environment

Abstract: A multistage decision process is a fuzzy mapping from X × UN → X where X and U are the state and policy spaces. Given the initial fuzzy set Si on X, the set of final fuzzy sets Sf on X has certain inclusive properties. Risk and optimum decisions are defined in terms of the inclusive properties.

Measurement in quantum mechanics as a stochastic process on spaces of fuzzy events

Abstract: The measurement of one or more observables can be considered to yield sample points which are in general fuzzy sets. Operationally these fuzzy sample points are the outcomes of calibration procedures undertaken to ensure the internal consistency of a scheme of measurement. By introducing generalized probability measures on σ-semifields of fuzzy events, one can view a quantum mechanical state as an ensemble of probability measures which specify the likelihood of occurrence of any specific fuzzy sample point at some instant. These sample points are the possible outcomes of any infinitely rapid succession of measurements at that instant of any sequence of observables of the system.

Experimental approach to fuzzy simulation of memorizing, forgetting and inference process

Abstract: Publisher Summary This chapter presents an approach of making fuzzy models of the memorizing-, forgetting- and inference processes that are essentially important in the human decision-making process. It illustrates a block diagram expression of a whole model of human decision making system, mapping expressions of experience process, memory process, and inference process based on memory. The chapter describes two types of fuzzy formulation of human decision-making. One is the decision-making based on memory only and the other is the one depending on both memory and inference based on memory. These processes are expressed by fuzzy relations. The chapter presents an experimental study to make a fuzzy model of memory process. It is found that the certainty degree of memory is a value of the membership function with its ambiguity and it varies with time either in the collapsing manner (forgetting) or in the emphasizing manner (sharpening). The certainty degree of memory and its ambiguity is a time function dependent on several subjective or objective factors governing the difficulty of memorizing.