scispace - formally typeset
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
More filters
Journal ArticleDOI

A reference points and intuitionistic fuzzy dominance based particle swarm algorithm for multi/many-objective optimization

TL;DR: A new loose Pareto dominant relationship named intuitionistic fuzzy dominance is adopted to research multi/many-objective particle swarm optimization problems and simulation results show that the proposed algorithm has better performance on most test problems.
Journal ArticleDOI

Analysis of Decision Making Operation In Cognitive Radio Using Fuzzy Logic System

TL;DR: This paper shows how fuzzy logic system can be used for decision making operation in cognitive radio, in which secondary user can use the spectrum effectively and gives the probability of the decision based on the three descriptive factors.
Journal ArticleDOI

The manipulation of images to handle indeterminacy in spatial reasoning

TL;DR: A new image-based method of reasoning, called ISR for indeterminacy in spatial reasoning, which dynamically constructs and inspects multiple images to reason about spatial prepositional phrases is proposed, which demonstrates that, with the help of specialized procedures, imagery can be more accurate for reasoning about spatially indeterminate descriptions.
Journal ArticleDOI

Design and modeling an Adaptive Neuro-Fuzzy Inference System (ANFIS) for the prediction of a security index in VANET

TL;DR: An applied Adaptive Neuro-Fuzzy Inference System (ANFIS) is proposed to obtain a prediction model of security index in VANET to estimate the network vulnerability in the event of an attack.

Color space analysis in color image segmentation

TL;DR: This report describes a novel method that includes color space pyramiding, low-pass filtering, 3-D object labeling and property calculation to acquire a proper number of colors and a good initial estimate of center positions, then fuzzy c-means algorithm can be used to optimally cluster the color space distribution points.
References
More filters
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.