ANN prediction models for indoor environment

Popescu, I; Nikitopoulos, D; Nafornita, I; Constantinou, P

dc.contributor.author	Popescu, I	en
dc.contributor.author	Nikitopoulos, D	en
dc.contributor.author	Nafornita, I	en
dc.contributor.author	Constantinou, P	en
dc.date.accessioned	2014-03-01T02:43:56Z
dc.date.available	2014-03-01T02:43:56Z
dc.date.issued	2006	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/31561
dc.subject	Artificial neural networks	en
dc.subject	Indoor channel characterization	en
dc.subject	Path loss models	en
dc.subject	Propagation prediction	en
dc.subject	Wireless communications	en
dc.subject.other	Mathematical models	en
dc.subject.other	Wireless telecommunication systems	en
dc.subject.other	Indoor channel characterization	en
dc.subject.other	Multilayer Perceptron	en
dc.subject.other	Path loss models	en
dc.subject.other	Neural networks	en
dc.title	ANN prediction models for indoor environment	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1109/WIMOB.2006.1696368	en
heal.identifier.secondary	http://dx.doi.org/10.1109/WIMOB.2006.1696368	en
heal.identifier.secondary	1696368	en
heal.publicationDate	2006	en
heal.abstract	This work presents the results of the studies concerning the application of the feedforward neural networks to the prediction of propagation path loss in indoor environment. The proposed models consist of a Multilayer Perceptron and a Generalized Regression Neural Network trained with measurements. The results of the prediction made by the proposed neural models show a good agreement with the measurements. ©2006 IEEE.	en
heal.journalName	IEEE International Conference on Wireless and Mobile Computing, Networking and Communications 2006, WiMob 2006	en
dc.identifier.doi	10.1109/WIMOB.2006.1696368	en
dc.identifier.spage	366	en
dc.identifier.epage	371	en