Modern machine learning (ML) techniques are making inroads in every aspect of renewable
energy for optimization and model prediction. The effective utilization of ML techniques for …

In this research, a groundbreaking intelligent model named the GWO-RF model is
introduced for the prediction of water inflow (WI) during tunnel construction. WI is a prevalent …

Big cities affected by intense mobility, traffic and pollution are adopting electrification-based
solutions for the reduction of the CO 2 emissions of combustion engines. An interesting field …

The sports industry features low energy intensity and low emissions through which it has
played an important role in realizing sustainable development. This study aims to examine …

The traditional manual approach of pavement condition evaluation is being replaced by
more sophisticated automated vehicle systems. Although these automated systems have …

Transportation sector is one of the major producers of greenhouse gases which are
responsible for climate change. Finding an appropriate emission estimation tool for large …

Droughts cause significant economic losses in many regions around the world, highlighting
a need to more accurately quantify implications of drought on production and water …

Eco-logistics, usually known as green logistics, refers to a set of sustainable policies and
initiatives targeted at lowering the environmental impact of this business's activities. This …

In this study, our primary objective was to analyze the tradeoff between accuracy and
complexity in machine learning models, with a specific focus on the impact of reducing …

The transfer city is a key point in air-to-rail intermodal travel (ARIT) that directly influences
the service level of the entire system. Although some studies have investigated factors that …