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 philosophical study on meaning and fuzzy sets
TL;DR: The meaning of fuzzy sets is reached from a new philosophical point of view by applying all three aspects of any use of a tool; being, change and meaning to a case of using fuzzy sets.
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Sensor resolution effect on fuzzy logic controller behaviour
E.M. Petrin,P. Wide,G. Eatherley +2 more
TL;DR: It is shown that it is possible to smooth this I/O characteristic of a fuzzy controller for truck and trailer docking by dithering the sensor data before their quantization.
A Diagnostic Evaluation For Microgravity and Radiation Against Immunity and Tumor in Space: A Fuzzy Logic Approach Engineering
TL;DR: In this article, a Mamdani model for diagnostic system by using Fuzzy Logic Toolbox in MATLAB was developed and two types of membership functions i.e. Triangular and Gaussian were used for as inputs to the system “gravity and radiations” risk factors were taken and the outputs were “Immunity and Tumor”.
Learning Emotions: A Software Engine for Simulating Realistic Emotion in Artificial Agents
TL;DR: This framework acts as a domain-independent, black-box solution for giving actors in games or simulations realistic emotional reactions to events, and uses a modified Fuzzy Logic Adaptive Model of Emotions model for emotion management.
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Facility Closeness Relationship Determination in the Construction Site
TL;DR: In this article, a fuzzy rule-based system developed in the manufacture industry is used to determine the facility closeness relationship in the construction site, with consideration of quantitative and qualitative factors.
References
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