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Research Article Open access CC BY 4.0

Effective Earth Radius Factor Prediction and Mapping for Ondo State, South Western Nigeria

A. O. Atijosan, R. A. Badru, K. H. Muibi, S. A. Ogunyemi, A. T. Alaga

Journal of Scientific Research and Reports · pp. 540–548 · Published 10 Apr 2015

10.9734/JSRR/2015/16160

Abstract

Accurate prediction and determination of the effective earth radius factor (k-factor) is critical for optimal performance in the design and planning of terrestrial line of sight communication links. In this work an artificial neural network (ANN) model is developed and used to predict k-factor values for four towns in Ondo State using satellite derived data. The towns are Okitipupa (6.5ºN, 4.78ºE), Ondo (7.11ºN, 4.83ºE), Akure (7.25ºN, 5.2ºE) and Ikare (7.52ºN, 5.75ºE). A feed forward back propagation ANN was implemented, thereafter trained, validated and tested using satellite derived data for the period from 1984 to 2002. Mean absolute error (MAE) was used to evaluate the performance of the ANN. The MAE values obtained were 0.0024, 0.0014, 0.002 and 0.003 for Okitipupa, Akure, Ikare and Ondo towns respectively. Contour map showing the predicted k-factor values interpolated over the map of Ondo state was plotted using Geographical Information System (GIS) techniques. The study concluded that ANN presents an effective means of predicting the average k-factor values over a geographical location.

Effective earth radius factor neural network GIS contour map.

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Cited by 3

Effective and Median Effective Earth Radius Factor Distribution Characterization for Microwave Link Design Applications

A. Nyete · 2021

A Neural Network-Based Method for Time Series Modeling of 3-D Atmospheric Refractivity Using Radio Occultation Measurements

J. Nzeagwu, J. Urama, A. Chukwude · IEEE Transactions on Geoscience and Remote Sensing · 2021

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