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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:

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Citations
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Forecasting Peak Load Electricity Demand Using Statistics and Rule Based Approach

TL;DR: In this article, the authors explored the development of rule-based method for forecasting electricity peak load demand, which synergized human reasoning style of fuzzy systems through the use of set of rules consisting of IF-THEN approximators with the learning and connectionist structure.
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Hybrid probabilistic fuzzy and non-probabilistic model of structural reliability

TL;DR: The results show that the presented hybrid model, which may ensure structural security, is effective and practical, and has broad applicability which can handle either linear or non-linear state functions.
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Prediction of wave parameters by using fuzzy inference system and the parametric models along the south coasts of the Black Sea

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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.