Open AccessBook
On fuzzy algorithms
Lotfi A. Zadeh
- pp 127-147
TLDR
A fuzzy algorithm is introduced which, though fuzzy rather than precise in nature, may eventually prove to be of use in a wide variety of problems relating to information processing, control, pattern recognition, system identification, artificial intelligence and, more generally, decision processes involving incomplete or uncertain data.Abstract:
Unlike most papers in Information and Control, our note contains no theorems and no proofs. Essentially, its purpose is to introduce a basic concept which, though fuzzy rather than precise in nature, may eventually prove to be of use in a wide variety of problems relating to information processing, control, pattern recognition, system identification, artificial intelligence and, more generally, decision processes involving incomplete or uncertain data. The concept in question will be called a fuzzy algorithm because it may be viewed as a generalization, through the process of fuzzification, of the conventional (nonfuzzy) conception of an algorithm. More specifically, unlike a nonfuzzy deterministic or nondeterministic algorithm (Floyd, 1967), a fuzzy algorithm may contain fuzzy statements, that is, statements containing names of fuzzy sets (Zadeh, 1965), by which we mean classes in which there may be grades of membership intermediate between full membership and nonmembership. To illustrate, fuzzy algorithms may contain fuzzy instructions such as:read more
Citations
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Sediment load prediction by combined fuzzy logic-wavelet method
TL;DR: In this article, a combination of wavelet and fuzzy logic techniques (WFL) is proposed as a new technique to model the behavior of sediment load, while the wavelet method is able to decompose the original series into its subbands, fuzzy logic method can be used as a predictive model for each subband.
Journal ArticleDOI
Fuzzy star functions, probabilistic automata, and their approximation by nonprobabilistic automata
TL;DR: The problem of approximating such functions (which can be defined, in particular, by probabilistic automata) by nonprobabilism automata is investigated, in several aspects.
Journal ArticleDOI
Fuzzy Turing Machines: Variants and Universality
TL;DR: It is shown that there is no universal FTM that can exactly simulate any FTM on it, but if the membership degrees of fuzzy sets are restricted to a fixed finite subset A of [0,1], such a universal machine exists.
"evaluation of teacher's performance using fuzzylogic techniques"
TL;DR: This paper explains the comparison of two different membership function and getting more or less similar so as to achieve the shape of membership function, which is not playing much role to evaluate the performance in positive or negative direction.
Journal ArticleDOI
Cooperative combinatorial optimization: evolutionary computation case study.
Mark Burgin,Eugene Eberbach +1 more
TL;DR: It is proved that evolutionary algorithms are more expressive than conventional recursive algorithms, such as Turing Machines, because they work toward a common optimization goal of the population using evolutionary computation techniques.
References
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Book
Fuzzy sets
TL;DR: A separation theorem for convex fuzzy sets is proved without requiring that the fuzzy sets be disjoint.
Journal ArticleDOI
On Computable Numbers, with an Application to the Entscheidungsproblem
TL;DR: This chapter discusses the application of the diagonal process of the universal computing machine, which automates the calculation of circle and circle-free numbers.
Journal ArticleDOI
L-fuzzy sets
TL;DR: This paper explores the foundations of, generalizes, and continues the work of Zadeh in [I] and [2].
Journal ArticleDOI
Nondeterministic Algorithms
TL;DR: Algorithms to solve combinatorial search problems by using multiple-valued functions are illustrated with algorithms to find all solutions to the eight queens problem on the chessboard, and to finding all simple cycles in a network.