Towards Utilization of Neurofuzzy Systems for Taxonomic Identification Using Psittacines as a Case Study. (21st February 2016)

• Record Type: Journal Article
• Authors: Rahimi, Shahram; Spiess, Cynthia R.; Gupta, Bidyut; Sahebkar, Elham
• Other Names: Liu Baoding Academic Editor.
• Is Part Of: Applied computational intelligence and soft computing. Volume 2016(2016)
• Publication Date: 2016-02-21
• Subjects: Computational intelligence -- Periodicals; Soft computing -- Periodicals; 006.305
• DOI: 10.1155/2016/6798905
• Languages: English
• ISSNs: 1687-9724

Abstract

Abstract : 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.