DocumentCode :
163824
Title :
A survey of diverse nature bio-inspired computing models
Author :
Kotteeswaran, C. ; Rajesh, A.
Author_Institution :
Bharath Univ., Chennai, India
fYear :
2014
fDate :
8-8 July 2014
Firstpage :
120
Lastpage :
124
Abstract :
Natural computing, also called Natural computation, is a recent emerging field of research that introduces three classes of methods: 1) a division of techniques which can be used to solve novel problems by retrieving inspiration from the nature; 2) a division that concentrates on the use of computers to synthesize natural observable fact; and 3) a division that employ natural materials (e.g., molecules) to compute. The main scheme of research that compose these three branches are artificial neural networks, evolutionary algorithms, swarm intelligence, artificial immune systems, fractal geometry, artificial life, DNA computing, and quantum computing, among others. In this paper, we make an attempt to investigate the working nature, applications, variants and generative power of various bio-inspired computing models such as membrane computing, splicing circular words, Bidirectional sticker system.
Keywords :
artificial immune systems; biocomputing; evolutionary computation; fractals; neural nets; quantum computing; swarm intelligence; DNA computing; artificial immune systems; artificial life; artificial neural networks; bidirectional sticker system; bioinspired computing models; evolutionary algorithms; fractal geometry; membrane computing; molecules; natural computation; natural computing; natural materials; quantum computing; splicing circular words; swarm intelligence; Automata; Biological system modeling; Biomembranes; Computational modeling; Conferences; Splicing; Bio-inspired Computing; Membrane Computing; Splicing Circular words; Watson crick two-way finite Automata;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Current Trends in Engineering and Technology (ICCTET), 2014 2nd International Conference on
Conference_Location :
Coimbatore
Print_ISBN :
978-1-4799-7986-8
Type :
conf
DOI :
10.1109/ICCTET.2014.6966273
Filename :
6966273
Link To Document :
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