ANN prediction models for outdoor environment

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

dc.contributor.author	Popescu, I	en
dc.contributor.author	Nikitopoulos, D	en
dc.contributor.author	Constantinou, P	en
dc.contributor.author	Nafornita, I	en
dc.date.accessioned	2014-03-01T02:43:57Z
dc.date.available	2014-03-01T02:43:57Z
dc.date.issued	2006	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/31562
dc.subject	Artificial Neural Network	en
dc.subject	Error Correction Model	en
dc.subject	Path Loss	en
dc.subject	Prediction Model	en
dc.subject	Root Mean Square Error	en
dc.subject	Standard Deviation	en
dc.subject	Theoretical Model	en
dc.subject	Mean Error	en
dc.subject	Neural Network	en
dc.subject	Neural Network Model	en
dc.subject.other	Artificial intelligence	en
dc.subject.other	Backpropagation	en
dc.subject.other	Computer networks	en
dc.subject.other	Error analysis	en
dc.subject.other	Error correction	en
dc.subject.other	Feedforward neural networks	en
dc.subject.other	Forecasting	en
dc.subject.other	Image classification	en
dc.subject.other	Mathematical models	en
dc.subject.other	Metropolitan area networks	en
dc.subject.other	Network protocols	en
dc.subject.other	Standards	en
dc.subject.other	Vegetation	en
dc.subject.other	Wireless networks	en
dc.subject.other	Artificial Neural Network (ANN) models	en
dc.subject.other	Artificial neural network (ANNs)	en
dc.subject.other	error correction models	en
dc.subject.other	Feed forward (FF)	en
dc.subject.other	International symposium	en
dc.subject.other	Mean error (ME)	en
dc.subject.other	Mobile radio communications	en
dc.subject.other	Neural network (NN) models	en
dc.subject.other	Outdoor environments	en
dc.subject.other	Path loss (PL)	en
dc.subject.other	prediction modeling	en
dc.subject.other	Propagation paths	en
dc.subject.other	Root mean-square error (RMSE)	en
dc.subject.other	Standard deviation (STD)	en
dc.subject.other	Neural networks	en
dc.title	ANN prediction models for outdoor environment	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1109/PIMRC.2006.254270	en
heal.identifier.secondary	4022648	en
heal.identifier.secondary	http://dx.doi.org/10.1109/PIMRC.2006.254270	en
heal.publicationDate	2006	en
heal.abstract	This paper presents the results of our studies concerning the applications of feedforward artificial neural networks to the propagation path loss prediction in outdoor environment. An error correction model is proposed, based on the combination between a theoretical model and a neural network. The performances of the proposed artificial neural network models are compared to the measured path loss values, based on the absolute mean error, standard deviation and root mean square error. Also, the proposed neural network models are compared to each other and to the COST 231-Walfisch-Ikegami. © 2006 IEEE.	en
heal.journalName	IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC	en
dc.identifier.doi	10.1109/PIMRC.2006.254270	en