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Toward utilization of neuro-fuzzy sy...

Southern Illinois University at Carbondale., Computer Science.

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Toward utilization of neuro-fuzzy systems for taxonomic identification using psittacines as a case study.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Toward utilization of neuro-fuzzy systems for taxonomic identification using psittacines as a case study./
Author:	Spiess, Cynthia R.
Description:	71 p.
Notes:	Adviser: Shahram Rahimi.
Contained By:	Masters Abstracts International47-01.
Subject:	Artificial Intelligence. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1456955
ISBN:	9780549734017

Toward utilization of neuro-fuzzy systems for taxonomic identification using psittacines as a case study.
Spiess, Cynthia R.

Toward utilization of neuro-fuzzy systems for taxonomic identification using psittacines as a case study. - 71 p.

Adviser: Shahram Rahimi.

Thesis (M.S.)--Southern Illinois University at Carbondale, 2008.

Demonstration of the neuro-fuzzy application NEFCLASS-J applied to the task of psittacine (parrot) taxonomic identification is presented in this thesis. Backgrounds on fuzzy logic and artificial neural networks along with methods to increase system accuracy are discussed. Neuro-fuzzy techniques are reviewed. The neuro-fuzzy systems ANFIS, GARIC, FUN, and SONFIN are briefly analyzed, followed by a more in-depth coverage of NEFCLASS-J. NEFCLASS-J is applied to parrot data for 141 and 183 groupings using 68 feature points or qualities. Results showed classification accuracies above 95% correct, which seem strongly tied to certain neuro-fuzzy system parameter values. Rule base sizes were in the range of (1,750, 1,950) rules. Better systems can probably be made with the help of experts from all the fields collaborating.

ISBN: 9780549734017Subjects--Topical Terms:

769149
Artificial Intelligence.

Toward utilization of neuro-fuzzy systems for taxonomic identification using psittacines as a case study.
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020 $a 9780549734017
035 $a (UMI)AAI1456955
035 $a AAI1456955
040 $a UMI $c UMI
100 1 $a Spiess, Cynthia R. $3 1035893
245 1 0 $a Toward utilization of neuro-fuzzy systems for taxonomic identification using psittacines as a case study.
300 $a 71 p.
500 $a Adviser: Shahram Rahimi.
500 $a Includes supplementary digital materials.
500 $a Source: Masters Abstracts International, Volume: 47-01, page: 0423.
502 $a Thesis (M.S.)--Southern Illinois University at Carbondale, 2008.
520 $a Demonstration of the neuro-fuzzy application NEFCLASS-J applied to the task of psittacine (parrot) taxonomic identification is presented in this thesis. Backgrounds on fuzzy logic and artificial neural networks along with methods to increase system accuracy are discussed. Neuro-fuzzy techniques are reviewed. The neuro-fuzzy systems ANFIS, GARIC, FUN, and SONFIN are briefly analyzed, followed by a more in-depth coverage of NEFCLASS-J. NEFCLASS-J is applied to parrot data for 141 and 183 groupings using 68 feature points or qualities. Results showed classification accuracies above 95% correct, which seem strongly tied to certain neuro-fuzzy system parameter values. Rule base sizes were in the range of (1,750, 1,950) rules. Better systems can probably be made with the help of experts from all the fields collaborating.
590 $a School code: 0209.
650 4 $a Artificial Intelligence. $3 769149
650 4 $a Biology, Bioinformatics. $3 1018415
650 4 $a Computer Science. $3 626642
690 $a 0715
690 $a 0800
690 $a 0984
710 2 $a Southern Illinois University at Carbondale. $b Computer Science. $3 1023716
773 0 $t Masters Abstracts International $g 47-01.
790 $a 0209
790 1 0 $a Carver, Norman F. $e committee member
790 1 0 $a Mogharreban, Namdar $e committee member
790 1 0 $a Rahimi, Shahram, $e advisor
791 $a M.S.
792 $a 2008
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1456955