Volume & Issue no: Volume 6, Issue 4, July - August 2017
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Title: |
Performance Evaluation of Soft Computing using Clustering Techniques |
Author Name: |
Dr. Suman Kumar Mishra, Mr. Shobhit Shukla |
Abstract: |
Abstract
Soft Computing can be considered as a tool to handle
inexactness and uncertainty. The main concept of soft
computing is to exploit the forbearance for inexactness,
uncertainty, fractional truth and approximation to accomplish
tractability, robustness and inexpensive solutions. It is used to
solve real life problems full of uncomfortable features due to
fractional, unclear, noisy and partial information. Clustering
gets its name as a metaphor for the soft computing. Clustering
aims to divide data groups into subgroups called clusters.
Clustering is still searching for killer applications that not only
takes advantage of its promise of "high performance and short
development lead time". This paper focuses on the evaluation of
the Genetic Algorithm concept of Soft Computing and measures
its performance using various clustering techniques.
Keywords: Soft Computing, Genetic Algorithms,
Clustering, K-means and K - means++. |
Cite this article: |
Dr. Suman Kumar Mishra, Mr. Shobhit Shukla , "
Performance Evaluation of Soft Computing using Clustering Techniques" , International Journal of Emerging Trends & Technology in Computer Science (IJETTCS) ,
Volume 6, Issue 4, July - August 2017 , pp.
017-020 , ISSN 2278-6856.
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