Analysis of some meteorological parameters using artificial neural network method for Makurdi, Nigeria | Zendy

Chukwu Chukwu | Zendy

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Analysis of some meteorological parameters using artificial neural network method for Makurdi, Nigeria

Author(s) -

Chukwu Chukwu

Publication year - 2012

Publication title -

african journal of environmental science and technology

Language(s) - English

Resource type - Journals

ISSN - 1996-0786

DOI - 10.5897/ajest11.350

Subject(s) - cloud cover , sunshine duration , relative humidity , mean squared error , artificial neural network , correlation coefficient , environmental science , meteorology , coefficient of determination , mathematics , atmospheric sciences , statistics , geography , computer science , cloud computing , geology , machine learning , operating system

The mean daily data for sunshine hours, maximum temperature, cloud cover and relative humidity data, were used to estimate monthly average global solar irradiation on a horizontal surface for Makurdi, Nigeria. The study used artificial neural networks (ANN) for the estimation. Results showed good agreement between the predicted and measured values of global solar irradiation. A correlation coefficient of 0.9982 was obtained with a maximum percentage error (MPE) of 0.8512 and root mean square error (RMSE) of 0.0032. The comparison between the ANN and some existing empirical models showed the advantage of the ANN prediction model. Key words: Sunshine hours, relative humidity, maximum temperature, cloudiness index, global solar radiation

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