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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A fuzzy AHP-based methodology for project prioritization and selection
Amir Shaygan,Özlem Müge Testik +1 more
TL;DR: A methodology based on fuzzy analytical hierarchy process (FAHP) for decision-making, integrated with cause-and-effect diagrams used in quality improvement studies, is proposed for this purpose.
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Back-driving a truck with suboptimal distance trajectories: a fuzzy logic control approach
Guanrong Chen,Delin Zhang +1 more
TL;DR: This paper provides a suboptimal solution to the problem of automatically back-driving a truck using the natural parabolic paths as the shortest moving distance requirement by applying fuzzy logic control techniques, which works well even without using a mathematical system model.
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Image thresholding by maximizing the index of nonfuzziness of the 2-D grayscale histogram
TL;DR: An image thresholding approach based on the index of nonfuzziness maximization of the 2-D grayscale histogram is proposed, which performs well and effectively but also is more robust when applied to noisy images.
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.
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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.