Advanced Extended Kohonen Mapping (EKM) modelling techniques for sensor actor networks

Chiu, C; Chaczko, Z; Moses, P

Advanced Extended Kohonen Mapping (EKM) modelling techniques for sensor actor networks

Chiu, C

Chaczko, Z

Moses, P

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Publication Type:: Conference Proceeding
Citation:: BROADBANDCOM 2009 - Selected Papers on Broadband Communication, Information Technology and Biomedical Applications, 2009, pp. 245 - 250
Issue Date:: 2009-01-01

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Field	Value	Language
dc.contributor.author	Chiu, C https://orcid.org/0000-0003-2045-5961	en_US
dc.contributor.author	Chaczko, Z https://orcid.org/0000-0002-2816-7510	en_US
dc.contributor.author	Moses, P	en_US
dc.date.issued	2009-01-01	en_US
dc.identifier.citation	BROADBANDCOM 2009 - Selected Papers on Broadband Communication, Information Technology and Biomedical Applications, 2009, pp. 245 - 250	en_US
dc.identifier.isbn	9788374934701	en_US
dc.identifier.uri	http://hdl.handle.net/10453/11205
dc.description.abstract	This paper discusses the results of utilising advanced EKM modelling techniques to manage Sensor-Actor networks (SANETs) such as wireless sensor networks. EKMs allow a quantitative analysis of an algorithmic artificial neural network process by using an indirect-mapping EKM to self-organise from a given input space to administer SANET routing and clustering functions with a control parameter space. Results demonstrate that in comparison to linear approximation techniques, indirect mapping with EKMs provide fluid control and feedback mechanisms by operating in a continuous sensory control space. SANETs can be designed for a variety of sensory perceptive contexts where interactive detection and optimisation of events are required for real-time environments.	en_US
dc.relation.ispartof	BROADBANDCOM 2009 - Selected Papers on Broadband Communication, Information Technology and Biomedical Applications	en_US
dc.title	Advanced Extended Kohonen Mapping (EKM) modelling techniques for sensor actor networks	en_US
dc.type	Conference Proceeding
utslib.for	0102 Applied Mathematics	en_US
dc.location.activity	Wroclaw, Poland	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 Design, Architecture and Building
pubs.organisational-group	/University of Technology Sydney/Faculty of Design, Architecture and Building/School of Architecture
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 Civil and Environmental Engineering
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - GBDTC - Global Big Data Technologies
pubs.organisational-group	/University of Technology Sydney/Strength - INEXT - Innovation in IT Services and Applications
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

This paper discusses the results of utilising advanced EKM modelling techniques to manage Sensor-Actor networks (SANETs) such as wireless sensor networks. EKMs allow a quantitative analysis of an algorithmic artificial neural network process by using an indirect-mapping EKM to self-organise from a given input space to administer SANET routing and clustering functions with a control parameter space. Results demonstrate that in comparison to linear approximation techniques, indirect mapping with EKMs provide fluid control and feedback mechanisms by operating in a continuous sensory control space. SANETs can be designed for a variety of sensory perceptive contexts where interactive detection and optimisation of events are required for real-time environments.

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

http://hdl.handle.net/10453/11205