Towards Utilization of Neurofuzzy Systems for Taxonomic Identification Using Psittacines as a Case Study
Demonstration of the neurofuzzy application to the task of psittacine (parrot) taxonomic identification is presented in this paper. In this work, NEFCLASS-J neurofuzzy system is utilized for classification of parrot data for 141 and 183 groupings, using 68 feature points or qualities. The reported r...
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Format: | Article |
Language: | English |
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Wiley
2016-01-01
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Series: | Applied Computational Intelligence and Soft Computing |
Online Access: | http://dx.doi.org/10.1155/2016/6798905 |
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author | Shahram Rahimi Cynthia R. Spiess Bidyut Gupta Elham Sahebkar |
author_facet | Shahram Rahimi Cynthia R. Spiess Bidyut Gupta Elham Sahebkar |
author_sort | Shahram Rahimi |
collection | DOAJ |
description | Demonstration of the neurofuzzy application to the task of psittacine (parrot) taxonomic identification is presented in this paper. In this work, NEFCLASS-J neurofuzzy system is utilized for classification of parrot data for 141 and 183 groupings, using 68 feature points or qualities. The reported results display classification accuracies of above 95%, which is strongly tied to the setting of certain parameters of the neurofuzzy system. Rule base sizes were in the range of 1,750 to 1,950 rules. |
format | Article |
id | doaj-art-2d918ea89d0d4b93822f886e1d52ddd0 |
institution | Kabale University |
issn | 1687-9724 1687-9732 |
language | English |
publishDate | 2016-01-01 |
publisher | Wiley |
record_format | Article |
series | Applied Computational Intelligence and Soft Computing |
spelling | doaj-art-2d918ea89d0d4b93822f886e1d52ddd02025-02-03T01:32:43ZengWileyApplied Computational Intelligence and Soft Computing1687-97241687-97322016-01-01201610.1155/2016/67989056798905Towards Utilization of Neurofuzzy Systems for Taxonomic Identification Using Psittacines as a Case StudyShahram Rahimi0Cynthia R. Spiess1Bidyut Gupta2Elham Sahebkar3Department of Computer Science, Southern Illinois University, Carbondale, IL 62901, USADepartment of Computer Science, Southern Illinois University, Carbondale, IL 62901, USADepartment of Computer Science, Southern Illinois University, Carbondale, IL 62901, USADepartment of Computer Science, University of Illinois Springfield, Springfield, IL 62703, USADemonstration of the neurofuzzy application to the task of psittacine (parrot) taxonomic identification is presented in this paper. In this work, NEFCLASS-J neurofuzzy system is utilized for classification of parrot data for 141 and 183 groupings, using 68 feature points or qualities. The reported results display classification accuracies of above 95%, which is strongly tied to the setting of certain parameters of the neurofuzzy system. Rule base sizes were in the range of 1,750 to 1,950 rules.http://dx.doi.org/10.1155/2016/6798905 |
spellingShingle | Shahram Rahimi Cynthia R. Spiess Bidyut Gupta Elham Sahebkar Towards Utilization of Neurofuzzy Systems for Taxonomic Identification Using Psittacines as a Case Study Applied Computational Intelligence and Soft Computing |
title | Towards Utilization of Neurofuzzy Systems for Taxonomic Identification Using Psittacines as a Case Study |
title_full | Towards Utilization of Neurofuzzy Systems for Taxonomic Identification Using Psittacines as a Case Study |
title_fullStr | Towards Utilization of Neurofuzzy Systems for Taxonomic Identification Using Psittacines as a Case Study |
title_full_unstemmed | Towards Utilization of Neurofuzzy Systems for Taxonomic Identification Using Psittacines as a Case Study |
title_short | Towards Utilization of Neurofuzzy Systems for Taxonomic Identification Using Psittacines as a Case Study |
title_sort | towards utilization of neurofuzzy systems for taxonomic identification using psittacines as a case study |
url | http://dx.doi.org/10.1155/2016/6798905 |
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