Influence of Training Set Selection in Artificial Neural Network-Based Propagation Path Loss Predictions


Autoria(s): Fernández Anitzine, Ignacio Ernesto; Romo Argota, Juan Antonio; Pérez Fontán, Fernando
Data(s)

31/05/2013

31/05/2013

2012

Resumo

This paper analyzes the use of artificial neural networks (ANNs) for predicting the received power/path loss in both outdoor and indoor links. The approach followed has been a combined use of ANNs and ray-tracing, the latter allowing the identification and parameterization of the so-called dominant path. A complete description of the process for creating and training an ANN-based model is presented with special emphasis on the training process. More specifically, we will be discussing various techniques to arrive at valid predictions focusing on an optimum selection of the training set. A quantitative analysis based on results from two narrowband measurement campaigns, one outdoors and the other indoors, is also presented.

Identificador

International Journal of Antennas and Propagation 2012 : (2012) // Article ID 351487

1687-5869

http://hdl.handle.net/10810/10176

10.1155/2012/351487

Idioma(s)

eng

Publicador

Hindawi Publishing Corporation

Relação

http://www.hindawi.com/journals/ijap/2012/351487/

Direitos

© 2012 Ignacio Fernández Anitzine et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

info:eu-repo/semantics/openAccess

Tipo

info:eu-repo/semantics/article