Diffraction Loss Prediction of Multiple Edges Using Bullington Method with Neural Network in Mountainous Areas

This paper proposes a neural network approach to improve the Bullington method by using parameters obtained from ignored obstacles in mountainous areas. Measurements were performed in mountainous areas to compare the prediction accuracy of propagation loss. And the measured data were used for neural...

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Main Authors: Changwon Lee, Sungkwon Park
Format: Article
Language:English
Published: Wiley 2018-01-01
Series:International Journal of Antennas and Propagation
Online Access:http://dx.doi.org/10.1155/2018/8737594
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author Changwon Lee
Sungkwon Park
author_facet Changwon Lee
Sungkwon Park
author_sort Changwon Lee
collection DOAJ
description This paper proposes a neural network approach to improve the Bullington method by using parameters obtained from ignored obstacles in mountainous areas. Measurements were performed in mountainous areas to compare the prediction accuracy of propagation loss. And the measured data were used for neural network training. A detailed description of the input parameters of the proposed neural network is presented. The prediction performances were improved by up to 3.20 dB in the average error and 2.11 dB in the standard deviation of errors by the proposed method when compared to traditional diffraction methods.
format Article
id doaj-art-b6887091dfb145c29d805274b00f6310
institution OA Journals
issn 1687-5869
1687-5877
language English
publishDate 2018-01-01
publisher Wiley
record_format Article
series International Journal of Antennas and Propagation
spelling doaj-art-b6887091dfb145c29d805274b00f63102025-08-20T02:23:08ZengWileyInternational Journal of Antennas and Propagation1687-58691687-58772018-01-01201810.1155/2018/87375948737594Diffraction Loss Prediction of Multiple Edges Using Bullington Method with Neural Network in Mountainous AreasChangwon Lee0Sungkwon Park1Department of Electronics and Computer Engineering, Hanyang University, Seoul 133-791, Republic of KoreaDepartment of Electronics and Computer Engineering, Hanyang University, Seoul 133-791, Republic of KoreaThis paper proposes a neural network approach to improve the Bullington method by using parameters obtained from ignored obstacles in mountainous areas. Measurements were performed in mountainous areas to compare the prediction accuracy of propagation loss. And the measured data were used for neural network training. A detailed description of the input parameters of the proposed neural network is presented. The prediction performances were improved by up to 3.20 dB in the average error and 2.11 dB in the standard deviation of errors by the proposed method when compared to traditional diffraction methods.http://dx.doi.org/10.1155/2018/8737594
spellingShingle Changwon Lee
Sungkwon Park
Diffraction Loss Prediction of Multiple Edges Using Bullington Method with Neural Network in Mountainous Areas
International Journal of Antennas and Propagation
title Diffraction Loss Prediction of Multiple Edges Using Bullington Method with Neural Network in Mountainous Areas
title_full Diffraction Loss Prediction of Multiple Edges Using Bullington Method with Neural Network in Mountainous Areas
title_fullStr Diffraction Loss Prediction of Multiple Edges Using Bullington Method with Neural Network in Mountainous Areas
title_full_unstemmed Diffraction Loss Prediction of Multiple Edges Using Bullington Method with Neural Network in Mountainous Areas
title_short Diffraction Loss Prediction of Multiple Edges Using Bullington Method with Neural Network in Mountainous Areas
title_sort diffraction loss prediction of multiple edges using bullington method with neural network in mountainous areas
url http://dx.doi.org/10.1155/2018/8737594
work_keys_str_mv AT changwonlee diffractionlosspredictionofmultipleedgesusingbullingtonmethodwithneuralnetworkinmountainousareas
AT sungkwonpark diffractionlosspredictionofmultipleedgesusingbullingtonmethodwithneuralnetworkinmountainousareas