Estimation of Refractivity. Estimation of Refractivity Using Artificial Neural Network and ITU-R models with Atmospheric Parameters At Nigeria

      Аннотация: The refractivity profile variation in tropospheric is one of the aspects that influences long-distance terrestrial electromagnetic wave propagation and performance of communication systems. This study is aimed at calculation and estimation of refractivity with tropospheric parameters of relative humidity, absolute temperature and atmospheric pressure using ITU-R model and artificial neural network model for January and October at Minna and Abuja, Nigeria. Validation results are thus, January at Minna: absolute temperature = 0.4313 K, relative humidity = 0.9989 %, pressure = 0.0201 (hpa), and October: absolute temperature = - 0.3146 K, relative humidity = 0.9597 % and pressure = 0.1962 respectively. While January at Abuja: absolute temperature = 0.6907 K, relative humidity = 0.9929 %, pressure = 0.3947 (hpa), and October: absolute temperature = - 0.4291 K, relative humidity = 0.9452 and pressure = -0.5344 respectively. The validation of the correlation coefficient results shows that all the tropospheric parameters have effects on refractivity, but relative humidity has more effect and is merely on October which was attributed to the large quantity of moisture at the troposphere

Ключевые слова: models, Artificial Neural Network, Atmosphere, refractivity, communicatiom