Half-hour global solar radiation forecasting based on static and dynamic multivariate neural networks
المؤلفون المشاركون
Jalal, Muhammad Ali
Zeroual, Abd al-Wahhab
Chabaa, Samirah
المصدر
Journal of Engineering Research
العدد
المجلد 9، العدد 2 (30 يونيو/حزيران 2021)، ص ص. 203-217، 15ص.
الناشر
جامعة الكويت مجلس النشر العلمي
تاريخ النشر
2021-06-30
دولة النشر
الكويت
عدد الصفحات
15
التخصصات الرئيسية
الملخص EN
Precise global solar radiation (GSR) measurements in a given location are very essential for designing and supervising solar energy systems.
in the case of rarity or absence of these measurements, it is important to have a theoretical or empirical model to compute the GSR values.
therefore, the main goal of this work is to offer, to designers and engineers of solar energy systems, an appropriate and accurate way to predict the half-hour global solar radiation (HHGSR) time series from some available meteorological parameters (relative humidity, air temperature, wind speed, precipitation, and acquisition time vector in half-hour scale).
for that purpose, two intelligent models are developed : the first one is a multivariate dynamic neural network with feedback connection, and the second is a multivariate static neural network.
the database used to build these models was recorded in Agdal's meteorological station in Marrakesh, Morocco, during the years of 2013 and 2014, and it was divided into two subsets.
the first subset is used for training and validating the models, and the second subset is used for testing the efficiency and the robustness of the developed models.
the obtained results, in terms of the statistical performance indicators, demonstrate the efficiency of the developed forecasting models to accurately predict the HHGSR parameter in the city of Marrakesh, Morocco.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Jalal, Muhammad Ali& Chabaa, Samirah& Zeroual, Abd al-Wahhab. 2021. Half-hour global solar radiation forecasting based on static and dynamic multivariate neural networks. Journal of Engineering Research،Vol. 9, no. 2, pp.203-217.
https://search.emarefa.net/detail/BIM-1494848
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Jalal, Muhammad Ali…[et al.]. Half-hour global solar radiation forecasting based on static and dynamic multivariate neural networks. Journal of Engineering Research Vol. 9, no. 2 (Jun. 2021), pp.203-217.
https://search.emarefa.net/detail/BIM-1494848
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Jalal, Muhammad Ali& Chabaa, Samirah& Zeroual, Abd al-Wahhab. Half-hour global solar radiation forecasting based on static and dynamic multivariate neural networks. Journal of Engineering Research. 2021. Vol. 9, no. 2, pp.203-217.
https://search.emarefa.net/detail/BIM-1494848
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references : p. 216-217
رقم السجل
BIM-1494848
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر