Prediction of solar direct irradiance in Iraq by using artificial neural network
Joint Authors
Muhammad, Zana Salim
Muhammad, Gzing Adil
Source
ZANCO Journal of Pure and Applied Sciences
Issue
Vol. 33, Issue 5 (31 Oct. 2021), pp.43-50, 8 p.
Publisher
Salahaddin University-Erbil Department of Scientific Publications
Publication Date
2021-10-31
Country of Publication
Iraq
No. of Pages
8
Main Subjects
Engineering & Technology Sciences (Multidisciplinary)
Abstract EN
Global solar irradiance is one of the main significant factors for designing and considering the volume of any solar station beside of it is usage in agricultural and building issue.
Due of lack a precise information about the irradiance in Iraq metrological organization and seismology, this study is aimed to adopt the historical global data, build numerical analysis via using artificial neural network and predicting hourly irradiance.
The test is applied over three locations Erbil, Bagdad, and Basra for being references to their closest locations.
A foreword neural network (FNN) is the learning algorithm that is used in this study with relying on seven input variables consisting of Temperature, Precipitation, Humidity, Wind speed, Wind direction Sunshine duration and Date.
After normalizing and standardizing data, an iteration method is used for determining the optimum number of neuron(s) in a hidden layer.
It yields a least Root Mean square error (RMSE) between 2.5 to 3.
The computed correlation coefficients are between 0.94 -0.96 for the mentioned locations.
American Psychological Association (APA)
Muhammad, Zana Salim& Muhammad, Gzing Adil. 2021. Prediction of solar direct irradiance in Iraq by using artificial neural network. ZANCO Journal of Pure and Applied Sciences،Vol. 33, no. 5, pp.43-50.
https://search.emarefa.net/detail/BIM-1388034
Modern Language Association (MLA)
Muhammad, Zana Salim& Muhammad, Gzing Adil. Prediction of solar direct irradiance in Iraq by using artificial neural network. ZANCO Journal of Pure and Applied Sciences Vol. 33, no. 5 (2021), pp.43-50.
https://search.emarefa.net/detail/BIM-1388034
American Medical Association (AMA)
Muhammad, Zana Salim& Muhammad, Gzing Adil. Prediction of solar direct irradiance in Iraq by using artificial neural network. ZANCO Journal of Pure and Applied Sciences. 2021. Vol. 33, no. 5, pp.43-50.
https://search.emarefa.net/detail/BIM-1388034
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 50
Record ID
BIM-1388034