论文信息 - Towards Utilization of Neurofuzzy Systems for Taxonomic Identification Using Psittacines as a Case Study

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 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.

[1] Rudolf Kruse,et al. NEFCLASS for Java-new learning algorithms , 1999, 18th International Conference of the North American Fuzzy Information Processing Society - NAFIPS (Cat. No.99TH8397).

[2] J. Ragle,et al. IUCN Red List of Threatened Species , 2010 .

[3] Marco Tomassini,et al. Soft computing - integrating evolutionary, neural, and fuzzy systems , 2001 .

[4] Michael Negnevitsky,et al. Artificial Intelligence: A Guide to Intelligent Systems , 2001 .

[5] Samarjit Kar,et al. Applications of neuro fuzzy systems: A brief review and future outline , 2014, Appl. Soft Comput..

[6] Chih-Feng Liu,et al. Application of type-2 neuro-fuzzy modeling in stock price prediction , 2012, Appl. Soft Comput..

[7] Christopher M. Bishop,et al. Neural networks for pattern recognition , 1995 .

[8] Rudolf Kruse,et al. NEFCLASS-J - A JAVA-Based Soft Computing Tool , 2000, Intelligent Systems and Soft Computing.

[9] J. Forshaw,et al. Parrots of the world : an identification guide , 2006 .

[10] A. K. Lohani,et al. Hydrological time series modeling: A comparison between adaptive neuro-fuzzy, neural network and autoregressive techniques , 2012 .