Application of Neural Network in Atmospheric Refractivity Profile at Makurdi

摘要：

　　The refractivity profile variation in troposphere is one of the aspects that influences long-distance terrestrial electromagnetic wave propagation and performance of communication systems.This study is aimed at calculating and estimating radio refractivity at Makurdi with tropospheric parameters of relative humidity,absolute temperature and atmospheric pressure using ITU-R and artificial neural network models.Validation results are thus,absolute temperature=0.4313 K,relative humidity=0.9989%,pressure=0.0201 (hpa) respectively.The validation of the correlation coefficient results shows that all the tropospheric parameters have effects on radio refractivity,but relative humidity has more effect which is attributed to the large quantity of moisture at the troposphere.From the estimation results,it is clear that artificial neural network has the capacity of estimating tropopheric refractivity since the estimated values has close agreement with the calculated values.

关键词： refractivity artificial neural network tropospheric ITU-R model

作者: Agbo G.A Ibeh G.F Onah D.U Umahi A.E Nnaji E Ugwuonah F.C

作者单位: Industrial Physics Department, Ebonyi State University, Abakaliki, Ebonyi State

会议类型: 国际会议

会议名称: 2013 International Conference on Information, Business and Education Technology (2013信息、商业与教育技术国际会议(ICIBET 2013))

会议地点: 北京

会议语种:英文

页码: 140-142

在线出版日期: 2013-03-14（万方平台首次上网日期，不代表论文的发表时间）