Productivity forecasting of solar distiller integrated with evacuated tubes and external condenser using artificial intelligence model and moth-flame optimizer

This paper aims at developing an artificial intelligence model to forecast the water yield of a modified solar distiller integrated with evacuated tubes and an external condenser. The model consists of a hybrid long short-term memory (LSTM) model optimized by a moth-flame optimizer (MFO) used as a s...

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Autores principales:	Ammar H. Elsheikh, Hitesh Panchal, Mahmoud Ahmadein, Ahmed O. Mosleh, Kishor Kumar Sadasivuni, Naser A. Alsaleh
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Solar distiller Evacuated tubes External condenser Forecasting Moth-flame optimizer LSTM neural Network Engineering (General). Civil engineering (General) TA1-2040
Acceso en línea:	https://doaj.org/article/7b27b3610543451bab385dc651ffc0fe
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Productivity forecasting of solar distiller integrated with evacuated tubes and external condenser using artificial intelligence model and moth-flame optimizer

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