The ANFIS system for nonlinear combined fore-casts in the telecommunications industry

Lin, CC; Lin, CL; Shyu, JZ; Lin, C

The ANFIS system for nonlinear combined fore-casts in the telecommunications industry

Lin, CC Lin, CL Shyu, JZ Lin, C

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Publisher:: ACTA Press
Publication Type:: Journal Article
Citation:: International Journal of Computers and Applications, 2012, 37 (12), pp. 30 - 35
Issue Date:: 2012-01-12

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Field	Value	Language
dc.contributor.author	Lin, CC	en_US
dc.contributor.author	Lin, CL	en_US
dc.contributor.author	Shyu, JZ	en_US
dc.contributor.author	Lin, C https://orcid.org/0000-0001-8371-8197	en_US
dc.date.issued	2012-01-12	en_US
dc.identifier.citation	International Journal of Computers and Applications, 2012, 37 (12), pp. 30 - 35	en_US
dc.identifier.issn	1206-212X	en_US
dc.identifier.uri	http://hdl.handle.net/10453/115477
dc.description.abstract	The Adaptive Network-Based Fuzzy Inference System (ANFIS) has been proven to be efficient for forecasting. To address this concern, this research develops a nonlinear combined forecasting system by ANFIS for predicting the demand of telecommu-nication technology. We investigate the weights assigned to the combined forecast using two linear methods (the Least squares analysis and the Logistic model), as well as one nonlinear me-thods (the Bass model). An empirical data set from 3G technol-ogy development in Taiwan is used to demonstrate the application of the proposed methodology. These results show that the ANFIS method outperforms other individual methods. Also, this proposed work also provides the user with a user interface in which user can fill the query and find the desired forecasting results.	en_US
dc.publisher	ACTA Press	en_US
dc.relation.ispartof	International Journal of Computers and Applications	en_US
dc.relation.isbasedon	10.5120/4740-6958	en_US
dc.subject.classification	Networking & Telecommunications	en_US
dc.title	The ANFIS system for nonlinear combined fore-casts in the telecommunications industry	en_US
dc.type	Journal Article
utslib.citation.volume	12	en_US
utslib.citation.volume	37	en_US
utslib.for	0805 Distributed Computing	en_US
utslib.for	1702 Cognitive Sciences	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
utslib.copyright.status	closed_access
pubs.consider-herdc	true	en_US
pubs.issue	12	en_US
pubs.publication-status	Published	en_US
pubs.volume	37	en_US

Abstract:

The Adaptive Network-Based Fuzzy Inference System (ANFIS) has been proven to be efficient for forecasting. To address this concern, this research develops a nonlinear combined forecasting system by ANFIS for predicting the demand of telecommu-nication technology. We investigate the weights assigned to the combined forecast using two linear methods (the Least squares analysis and the Logistic model), as well as one nonlinear me-thods (the Bass model). An empirical data set from 3G technol-ogy development in Taiwan is used to demonstrate the application of the proposed methodology. These results show that the ANFIS method outperforms other individual methods. Also, this proposed work also provides the user with a user interface in which user can fill the query and find the desired forecasting results.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/115477