Statistics show that developed countries already host a significant number of building
integrated photovoltaic/thermal (BIPV/T) systems, but develo** countries, including many …

Due to the recent advancements in the Internet of Things and data science techniques, a
wide range of studies have investigated the use of data mining (DM) and machine learning …

This paper presents data-driven models for photovoltaic module temperature prediction and
analyzes the relation and effects of ambient conditions to module temperature. A total of 12 …

There is a growing effort towards the application of solar technologies to meet electrical and
thermal demand. However, substantial energy is used in buildings around the world for …

Bckground The flow of nanofluids is extremely pertinent because of its significant heat
transport capabilities and notable industrial application. In an effort to improve heat transfer …

This study investigates the effects of absorber design on the performance of a water-based
photovoltaic thermal collector (PVT). In this regard, three different absorber designs with the …

Abstract Background Lithium-ion (Li-ion) batteries are one of the most attractive and
promising energy storage systems that emerge in different industrial sectors–at the top of …

In this work, as an extension of previous machine learning studies, three novel techniques,
namely local interpretable model-agnostic explanations (LIME), neural network pattern …

Solar stills provide a promising avenue for freshwater production in regions grappling with
water scarcity, especially remote locales. However, their efficiency is often constrained by …

Landslides seriously threaten human life and property. The rapid and accurate prediction of
landslide geological hazard susceptibility is the key to disaster prevention and mitigation …