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Distribution analysis and autoregressive modelling of ultraviolet radiation over Akure,Nigeria

机译:尼日利亚Akure紫外线辐射分配分析与自回归建模

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摘要

Management of health risks associated with excessive exposure to ultraviolet radiation involves understanding its characteristics within any location. This work employed five-year archived data of UV index for analysis and autoregressive modelling of ultraviolet radiation over Akure (7.15°N, 5.12°E), Nigeria. In-situ measurements of UV index were made every day between January 2007 and December 2011 at 30 min interval using Davis 6162 vantage Pro2 weather station. Prevalence of high intensity UV index, which indicates human susceptibility to UV-related health risks was investigated. The statistical model that best describes UV distribution and its autoregressive characteristics were also determined for the location. Annual UV index was found to fit a Nakagami distribution and well modelled by a 3rd order polynomial equation to at least 95% accuracy. Non-linear autoregressive (NAR) artificial neural network (ANN) analysis also returned regression coefficient values of 0.95, 0.94 and 0.94 for each of training, validation and test parameters respectively.
机译:与过度暴露于紫外线辐射相关的健康风险管理涉及理解其在任何位置内的特征。这项工作采用了五年的紫外线指数的归档数据,用于尼日利亚的紫外线辐射紫外线辐射进行分析和自动评级建模。使用DAVIS 6162 Vantage Pro2气象站的30分钟间隔,每天在2011年1月和2011年12月之间每天进行UV指数的原位测量。研究了高强度紫外线指数的患病率,表明人类对紫外线相关的健康风险的敏感性。还确定了最能描述紫外线分布及其自回归特性的统计模型。发现年度紫外线指数适合Nakagami分布,并通过第三阶多项式方程建模良好,以至少为95%的精度。非线性自回归(NAR)人工神经网络(ANN)分析还分析了每个训练,验证和测试参数的回归系数值0.95,0.94和0.94。

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