ISSN: 2375-2998
International Journal of Electrical and Electronic Science  
Manuscript Information
 
 
Rain Attenuation Prediction in Nigeria Using Artificial Neural Network (ANN)
International Journal of Electrical and Electronic Science
Vol.6 , No. 1, Publication Date: Apr. 9, 2019, Page: 1-7
902 Views Since April 9, 2019, 983 Downloads Since Apr. 9, 2019
 
 
Authors
 
[1]    

Ibukun Daniel Olatunde, Department of Physics with Electronics, Oduduwa University Ipetumodu, Ile Ife, Osun State, Nigeria.

[2]    

Kazeem Oladele Babatunde, Department of Physics with Electronics, Oduduwa University Ipetumodu, Ile Ife, Osun State, Nigeria.

[3]    

David Oluwarotimi Afolabi, Department of Physics with Electronics, Oduduwa University Ipetumodu, Ile Ife, Osun State, Nigeria.

 
Abstract
 

The prediction of rain rate and rain attenuation plays an essential role in the fields of communications, agriculture, military services, etc. This work presents rain attenuation prediction in Nigeria using Artificial Neural Network (ANN). Rainfall data of ten years were collected from measurements made in six different geographical locations. The locations include Enugu (east), Ikeja (south-west), Kano (north-west), Lokoja (north-central), Maiduguri (north-east) and Port-Harcourt (south-south). These locations represent all geographical areas in Nigeria. ANN was trained to predict rain attenuation in these locations using the annual rainfall data given from 2007 to 2016. Conversely, the ANN was trained with sets of data from the year 2007 to 2013, thus, the result of the training was used to predict rain attenuation from the year 2014 to 2016. The rain attenuation results given by ANN were compared to the results given by the International Telecommunication Union (ITU) model which is a well-established model. The results in terms of the mean squared error (MSE) performance show that ANN predicted attenuation agrees closely with the ITU model prediction. Conversely, the resulted ANN training is a useful tool for communication engineers and expatriates to predict rainfall attenuation of subsequent years and to proactively solve the inherent signal attenuation problem facing satellite-to-earth path operation above 10GHz.


Keywords
 

Rain Attenuation, Rain Rate, ANN, ITU Model, Mean Squared Error


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