Accurate forecasts of future energy usage are an important step towards reaching carbon
mitigation commitments for city policymakers. Beyond identifying sources of emission …

Building energy forecasting methodologies utilized by municipal governments tend to be
geared heavily towards depicting broader qualitative representations of regional change …

Sustainability policies to mitigate transportation energy impacts on the urban environment
are urgently needed. Energy prediction models provide critical information to decision …

The transportation sector is deemed one of the primary sources of energy consumption and
greenhouse gases throughout the world. To realise and design sustainable transport, it is …

Energy consumption prediction is an integral part of planning and controlling energy used in
the building sector which accounts for 40% of the global energy consumption and a …

This paper presents four modeling techniques for predicting household transportation
energy consumption by exploring decision trees, random forest, and neural networks in …

This study examines the vital role of accurate load forecasting in the energy planning of
smart cities. It introduces a hybrid approach that uses machine learning (ML) to forecast …

Fuel consumption modeling using real-world collected driving data has been at the center of
recent research, due to the emergence of low-cost driving data collection sensors. In this …

The study presents a novel framework integrating feature selection (FS) and machine
learning (ML) techniques to forecast inland national energy consumption (EC) in the United …

The road transportation sector in Saudi Arabia has been observing a surging growth of
demand trends for the last couple of decades. The main objective of this article is to extract …