Muhammed A. Hassan
Assistant Professor of Mechanical Power Engineering
(email)
Neural network
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Hassan, M. A., and D. Banerjee,
"
A soft computing approach for estimating the specific heat capacity of molten salt-based nanofluids
",
Journal of Molecular Liquids
, vol. 281, pp. 365–375, 2019.
Hassan, M. A., A. Khalil, S. Kaseb, and M. A. Kassem,
"
Potential of four different machine-learning algorithms in modeling daily global solar radiation
",
Renewable Energy
, vol. 111, pp. 52-62, 2017.
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Algerian Big South
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ANFIS
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control
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Day number
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Decision trees
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Desert climate
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Empirical models
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Global radiation
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Global solar radiation
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Independent model
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K-fold cross-validation
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Machine learning
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Molten salt
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Nanofluids
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Neural network
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parabolic trough collectors
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performance
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Regression analysis
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simulation
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sizing
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solar energy
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Solar radiation
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Specific heat capacity
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storage tank
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Support Vector Machines
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thermal stratification
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tracking configuration
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Recent Publications
Assessment of a multiple port storage tank in a CPC-driven solar process heat system
Ultra-short-term exogenous forecasting of photovoltaic power production using genetically optimized non-linear auto-regressive recurrent neural networks
Sleeping pods with radiant cooling panels: A first assessment of thermal comfort and cooling capacity
Sensors selection for tool failure detection during machining processes: A simple accurate classification model
Selection methodology of representative meteorological days for assessment of renewable energy systems
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