Applications of generalized RBF-NN for path loss prediction

Popescu, I; Kanatas, A; Angelou, E; Nafornita, I; Constantinou, P

dc.contributor.author	Popescu, I	en
dc.contributor.author	Kanatas, A	en
dc.contributor.author	Angelou, E	en
dc.contributor.author	Nafornita, I	en
dc.contributor.author	Constantinou, P	en
dc.date.accessioned	2014-03-01T02:42:04Z
dc.date.available	2014-03-01T02:42:04Z
dc.date.issued	2002	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/30762
dc.subject	Channel characterization	en
dc.subject	Neural networks	en
dc.subject	Propagation path loss models	en
dc.subject.other	Channel characterization	en
dc.subject.other	Error control	en
dc.subject.other	Hybrid prediction models	en
dc.subject.other	Mean errors	en
dc.subject.other	Neural models	en
dc.subject.other	Path loss	en
dc.subject.other	Path loss prediction	en
dc.subject.other	Propagation paths	en
dc.subject.other	Radial basis function neural networks	en
dc.subject.other	Root mean square errors	en
dc.subject.other	Standard deviation	en
dc.subject.other	Forecasting	en
dc.subject.other	Mathematical models	en
dc.subject.other	Radial basis function networks	en
dc.subject.other	Radio communication	en
dc.subject.other	Neural networks	en
dc.title	Applications of generalized RBF-NN for path loss prediction	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1109/PIMRC.2002.1046748	en
heal.identifier.secondary	http://dx.doi.org/10.1109/PIMRC.2002.1046748	en
heal.identifier.secondary	1046748	en
heal.publicationDate	2002	en
heal.abstract	This paper presents the results of the Generalized Radial Basis Function Neural Networks applications for the prediction of propagation path loss in urban and suburban environment. We have studied two types of neural network based models; the first one is used for path loss prediction while the second one is a hybrid prediction model based on error control. The performances of the neural models are compared to the path loss values measured in the city of Kavala and in Oia village on Santorini Island, Greece, based on the absolute mean error, standard deviation and root mean square error between predicted and measured values. ©2002 IEEE.	en
heal.journalName	IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC	en
dc.identifier.doi	10.1109/PIMRC.2002.1046748	en
dc.identifier.volume	1	en
dc.identifier.spage	484	en
dc.identifier.epage	488	en