Determining the Factors Affecting the Boiling Heat Transfer Coefficient of Sintered Coated Porous Surfaces by Uzair Sajjad (19646296)

“…In this regard, two Bayesian optimization algorithms including Gaussian process regression (GPR) and gradient boosting regression trees (GBRT) are used for tuning the hyper-parameters (number of input and dense nodes, number of dense layers, activation function, batch size, Adam decay, and learning rate) of the deep neural network. …”

Optimizing overheating, lighting, and heating energy performances in Canadian school for climate change adaptation: Sensitivity analysis and multi-objective optimization methodolog... by Mutasim Baba, Fuad

“…This paper aims to search for the optimum school building design under three simultaneous conflicting objective functions: (1) the minimization of overheating hours to less than 40 h as required by Building Bulletin BB101 building code by using passive mitigation measures, (2) the minimization of heating energy use to less than 15 kW/m2 ac cording to passive house requirements and thus the reduction of greenhouse gas emissions, and (3) the mini mization of artificial lighting energy use to less than the current lighting energy use by maximization of daylighting usage without exceeding acceptable glare index in classrooms. …”
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Impact of fuzzy volume fraction on unsteady stagnation-point flow and heat transfer of a third-grade fuzzy hybrid nanofluid over a permeable shrinking/stretching sheet by Imran Siddique (12705185)

“…Also, the comparison of A⁢l₂⁢O₃/SA, Cu/SA and A⁢l_2⁢O₃ +Cu/SA through the fuzzy membership functions (MFs). The fuzzy MFs show that the hybrid nanofluid (A⁢l₂⁢O₃ +Cu/SA) in terms of rate of heat transfer is better than both Cu/SA and A⁢l_2⁢O₃/SA nanofluids.…”