A Comparative Study of KBS, ANN and Statistical Clustering Techniques for Unattended Stellar Classification
The purpose of this work is to present a comparative analysis of knowledge-based systems, artificial neural networks and statistical clustering algorithms applied to the classification of low resolution stellar spectra. These techniques were used to classify a sample of approximately 258 optical spe...
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| creator | Dafonte, Carlos Rodríguez, Alejandra Arcay, Bernardino Carricajo, Iciar Manteiga, Minia |
| description | The purpose of this work is to present a comparative analysis of knowledge-based systems, artificial neural networks and statistical clustering algorithms applied to the classification of low resolution stellar spectra. These techniques were used to classify a sample of approximately 258 optical spectra from public catalogues using the standard MK system. At present, we already dispose of a hybrid system that carries out this task, applying the most appropriate classification method to each spectrum with a success rate that is similar to that of human experts. |
| doi_str_mv | 10.1007/11578079_59 |
| format | Book Chapter |
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These techniques were used to classify a sample of approximately 258 optical spectra from public catalogues using the standard MK system. At present, we already dispose of a hybrid system that carries out this task, applying the most appropriate classification method to each spectrum with a success rate that is similar to that of human experts.</description><subject>Applied sciences</subject><subject>Artificial intelligence</subject><subject>Computer science; control theory; systems</subject><subject>Exact sciences and technology</subject><subject>Expert System</subject><subject>Human Expert</subject><subject>Input Pattern</subject><subject>Pattern recognition. Digital image processing. 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Computational geometry</topic><topic>Spectral Parameter</topic><topic>Spectral Type</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Dafonte, Carlos</creatorcontrib><creatorcontrib>Rodríguez, Alejandra</creatorcontrib><creatorcontrib>Arcay, Bernardino</creatorcontrib><creatorcontrib>Carricajo, Iciar</creatorcontrib><creatorcontrib>Manteiga, Minia</creatorcontrib><collection>Pascal-Francis</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Dafonte, Carlos</au><au>Rodríguez, Alejandra</au><au>Arcay, Bernardino</au><au>Carricajo, Iciar</au><au>Manteiga, Minia</au><au>Sanfeliu, Alberto</au><au>Cortés, Manuel Lazo</au><format>book</format><genre>bookitem</genre><ristype>CHAP</ristype><atitle>A Comparative Study of KBS, ANN and Statistical Clustering Techniques for Unattended Stellar Classification</atitle><btitle>Lecture notes in computer science</btitle><seriestitle>Lecture Notes in Computer Science</seriestitle><date>2005</date><risdate>2005</risdate><spage>566</spage><epage>577</epage><pages>566-577</pages><issn>0302-9743</issn><eissn>1611-3349</eissn><isbn>9783540298502</isbn><isbn>3540298509</isbn><eisbn>9783540322429</eisbn><eisbn>3540322426</eisbn><abstract>The purpose of this work is to present a comparative analysis of knowledge-based systems, artificial neural networks and statistical clustering algorithms applied to the classification of low resolution stellar spectra. 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| fulltext | fulltext |
| identifier | ISSN: 0302-9743 |
| ispartof | Lecture notes in computer science, 2005, p.566-577 |
| issn | 0302-9743 1611-3349 |
| language | eng |
| recordid | cdi_pascalfrancis_primary_17372749 |
| source | Springer Books |
| subjects | Applied sciences Artificial intelligence Computer science control theory systems Exact sciences and technology Expert System Human Expert Input Pattern Pattern recognition. Digital image processing. Computational geometry Spectral Parameter Spectral Type |
| title | A Comparative Study of KBS, ANN and Statistical Clustering Techniques for Unattended Stellar Classification |
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