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Volume & Issue no: Volume 4, Issue 1, January - February 2015

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Title:
Quasar Candidate Selection by Clustering using Fibonacci Series for Astronomical Surveys
Author Name:
Rohit K. Chandran, Ms. S. S. Pawar
Abstract:
Abstract It is becoming apparent that the next generation astronomical analysis requires good domain knowledge to handle vast amount of astronomical data over network. The data availability over internet has increased tremendously and there exist a bridging gap between Computer Scientists and Astronomers. Most of the conventional methods are directly applied to the data without any simplification mechanism. The K-means is a clustering algorithm that has been used widely to classify dataset in astronomical databases. In this paper we propose an approach to group Quasar candidates with redshirts varying between 0.8 and 2.2 from SDSS catalogue. Most of these Quasars lie within a single region in a color versus red shift plot. For clustering, A similarity matrix is generated based on its photometric properties using their nonstellar colors ugriz photometry from SDSS Dataset. Clustering is performed on this matrix along with red shift. This matrix derived consists of score based on structured scientific information that leads to find interdependencies within the astronomical domain. The matrix eases the process of clustering by reducing number of attributes within each instance. The improvement in clustering performance can be understood when the inputs are of large scale. Keywords: Data Mining, Astro-informatics, Clustering, Similarity evaluation, Fibonacci Series.
Cite this article:
Rohit K. Chandran, Ms. S. S. Pawar , " Quasar Candidate Selection by Clustering using Fibonacci Series for Astronomical Surveys " , International Journal of Emerging Trends & Technology in Computer Science (IJETTCS) , Volume 4, Issue 1, January - February 2015 , pp. 226-230 , ISSN 2278-6856.
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International Journal of Emerging Trends & Technology in Computer Science (IJETTCS)
ISSN 2278-6856
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