Application of Hybrid ARIMA and Artificial Neural Network Modelling for Electromagnetic Propagation: An Alternative to the Least Squares Method and ITU Recommendation P.1546-5 for Amazon Urbanized Cities
This study sets out an empirical hybrid autoregressive integrated moving average (ARIMA) and artificial neural network (ANN) model designed to estimate electromagnetic wave propagation in densely forested urban areas. Received signal power intensity data was acquired through measurement campaigns ca...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | International Journal of Antennas and Propagation |
| Online Access: | http://dx.doi.org/10.1155/2020/8494185 |
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| author | Ramz L. Fraiha Lopes Simone G. C. Fraiha Herminio S. Gomes Vinicius D. Lima Gervasio P. S. Cavalcante |
| author_facet | Ramz L. Fraiha Lopes Simone G. C. Fraiha Herminio S. Gomes Vinicius D. Lima Gervasio P. S. Cavalcante |
| author_sort | Ramz L. Fraiha Lopes |
| collection | DOAJ |
| description | This study sets out an empirical hybrid autoregressive integrated moving average (ARIMA) and artificial neural network (ANN) model designed to estimate electromagnetic wave propagation in densely forested urban areas. Received signal power intensity data was acquired through measurement campaigns carried out in the Metropolitan Area of Belém (MAB), in the Brazilian Amazon. Comparisons were made between estimates from classical least squares (LS) fitting and ITU (International Telecommunication Union) recommendation P. 1546-5. The results indicate the model is, at least, 44% more precise than every ITU estimate and, in some situations, is at least 11% better than an LS estimate, depending on the respective values of the relative error (RE). |
| format | Article |
| id | doaj-art-7c8e830960f448b1956e635ca5e69747 |
| institution | OA Journals |
| issn | 1687-5869 1687-5877 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Antennas and Propagation |
| spelling | doaj-art-7c8e830960f448b1956e635ca5e697472025-08-20T02:07:25ZengWileyInternational Journal of Antennas and Propagation1687-58691687-58772020-01-01202010.1155/2020/84941858494185Application of Hybrid ARIMA and Artificial Neural Network Modelling for Electromagnetic Propagation: An Alternative to the Least Squares Method and ITU Recommendation P.1546-5 for Amazon Urbanized CitiesRamz L. Fraiha Lopes0Simone G. C. Fraiha1Herminio S. Gomes2Vinicius D. Lima3Gervasio P. S. Cavalcante4Post Graduation Program in Eletrical Engineering (PPGEE), Federal University of Pará (UFPA), Belém 66075-110, BrazilPost Graduation Program in Eletrical Engineering (PPGEE), Federal University of Pará (UFPA), Belém 66075-110, BrazilPost Graduation Program in Eletrical Engineering (PPGEE), Federal University of Pará (UFPA), Belém 66075-110, BrazilPost Graduation Program in Eletrical Engineering (PPGEE), Federal University of Pará (UFPA), Belém 66075-110, BrazilPost Graduation Program in Eletrical Engineering (PPGEE), Federal University of Pará (UFPA), Belém 66075-110, BrazilThis study sets out an empirical hybrid autoregressive integrated moving average (ARIMA) and artificial neural network (ANN) model designed to estimate electromagnetic wave propagation in densely forested urban areas. Received signal power intensity data was acquired through measurement campaigns carried out in the Metropolitan Area of Belém (MAB), in the Brazilian Amazon. Comparisons were made between estimates from classical least squares (LS) fitting and ITU (International Telecommunication Union) recommendation P. 1546-5. The results indicate the model is, at least, 44% more precise than every ITU estimate and, in some situations, is at least 11% better than an LS estimate, depending on the respective values of the relative error (RE).http://dx.doi.org/10.1155/2020/8494185 |
| spellingShingle | Ramz L. Fraiha Lopes Simone G. C. Fraiha Herminio S. Gomes Vinicius D. Lima Gervasio P. S. Cavalcante Application of Hybrid ARIMA and Artificial Neural Network Modelling for Electromagnetic Propagation: An Alternative to the Least Squares Method and ITU Recommendation P.1546-5 for Amazon Urbanized Cities International Journal of Antennas and Propagation |
| title | Application of Hybrid ARIMA and Artificial Neural Network Modelling for Electromagnetic Propagation: An Alternative to the Least Squares Method and ITU Recommendation P.1546-5 for Amazon Urbanized Cities |
| title_full | Application of Hybrid ARIMA and Artificial Neural Network Modelling for Electromagnetic Propagation: An Alternative to the Least Squares Method and ITU Recommendation P.1546-5 for Amazon Urbanized Cities |
| title_fullStr | Application of Hybrid ARIMA and Artificial Neural Network Modelling for Electromagnetic Propagation: An Alternative to the Least Squares Method and ITU Recommendation P.1546-5 for Amazon Urbanized Cities |
| title_full_unstemmed | Application of Hybrid ARIMA and Artificial Neural Network Modelling for Electromagnetic Propagation: An Alternative to the Least Squares Method and ITU Recommendation P.1546-5 for Amazon Urbanized Cities |
| title_short | Application of Hybrid ARIMA and Artificial Neural Network Modelling for Electromagnetic Propagation: An Alternative to the Least Squares Method and ITU Recommendation P.1546-5 for Amazon Urbanized Cities |
| title_sort | application of hybrid arima and artificial neural network modelling for electromagnetic propagation an alternative to the least squares method and itu recommendation p 1546 5 for amazon urbanized cities |
| url | http://dx.doi.org/10.1155/2020/8494185 |
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