The presence of magnetic field results in a reduction in natural convective heat transfer and
entropy generation in cavities. The use of nanofluids improves the performance of thermal …

Beginning in the early 1990s, photovoltaic (PV) technologies were integrated with building
envelopes to reduce peak electrical load and fulfill building energy demands. The PV …

In the present study, using 15 machine learning algorithms (MLP, SVM, RBF, ELM, ANFIS, D-
Tree, MLR, MPR, BPNN, BN, LM, GD, BFGS, XGB and GMDH), the rheological behavior of …

Recently, due to the increasing demand for energy and the identification of fossil fuels and
their pollution, the focus on renewable energy is increasing day by day, so the use of …

Environmental air pollutants pose a serious threat to human society's health and way of life,
and their amount is rising quickly. Given that we spend the majority of our time indoors, good …

In this article, the ability of GMDH artificial neural networks (ANNs) to predict the rheological
behavior (RB) of nanofluids (NFs) containing CuO NPs is studied. ANNs are a powerful …

This study predicts the parameters such as viscosity and thermal conductivity in silica-
alumina-MWCN/water nanofluid using the artificial intelligence method and using design …

As the transport sector is responsible for the consumption of a vast proportion of the oil
produced, it is mandatory to research feasible solutions to tackle this issue. The application …

The entering sunlight from the building's windows mainly affects the heating and visual
comfort of the occupants. The applications of Venetian blinds are a solution to improve the …

One of the important categories in office spaces is the control of daylight and energy
consumption. By controlling natural light, it is possible to provide uniform light in the entire …