DocumentCode
3410858
Title
Advances in Fuzzy Method for Natural Computing
Author
Zhang, Jing
Author_Institution
Beijing Union Univ., Beijing, China
Volume
2
fYear
2009
fDate
12-14 Aug. 2009
Firstpage
18
Lastpage
23
Abstract
Both natural computing and fuzzy method exhibit human-like mental processing. Natural computing is the field of research that works with computational techniques inspired in part by natural systems. Fuzzy method is an alternative to traditional notions of set membership and logic, and it occurs in many applications of engineering, science and medicine. This paper presents a survey of recent advances in fuzzy method for natural computing, such as fuzzy artificial neural networks, fuzzy genetic algorithms, fuzzy ant colony optimization, fuzzy artificial immune systems, etc. We utilize uncertainty handling capacity of fuzzy method for modeling ambiguity, and the learning ability of natural computing for efficiently traversing large search spaces.
Keywords
artificial immune systems; fuzzy logic; fuzzy neural nets; fuzzy set theory; genetic algorithms; learning (artificial intelligence); search problems; uncertainty handling; computational technique; fuzzy ant colony optimization; fuzzy artificial immune system; fuzzy artificial neural network; fuzzy genetic algorithm; fuzzy logic; fuzzy natural computing hybrid technique; fuzzy set membership; human-like mental processing; learning ability; modeling ambiguity; traversing large search space; uncertainty handling capacity; Ant colony optimization; Artificial immune systems; Artificial neural networks; Computer networks; Fuzzy logic; Fuzzy neural networks; Fuzzy sets; Fuzzy systems; Genetic algorithms; Uncertainty; fuzzy ant colony optimization; fuzzy artificial immune systems; fuzzy artificial neural networks; fuzzy genetic algorithms; fuzzy method; natural computing;
fLanguage
English
Publisher
ieee
Conference_Titel
Hybrid Intelligent Systems, 2009. HIS '09. Ninth International Conference on
Conference_Location
Shenyang
Print_ISBN
978-0-7695-3745-0
Type
conf
DOI
10.1109/HIS.2009.116
Filename
5254412
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