[HTML][HTML] An interpretable multi-stage forecasting framework for energy consumption and CO2 emissions for the transportation sector

Q Qiao, H Eskandari, H Saadatmand, MA Sahraei - Energy, 2024 - Elsevier
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 …

Peeking inside the black-box: Explainable machine learning applied to household transportation energy consumption

SS Amiri, S Mottahedi, ER Lee, S Hoque - Computers, Environment and …, 2021 - Elsevier
Sustainability policies to mitigate transportation energy impacts on the urban environment
are urgently needed. Energy prediction models provide critical information to decision …

Prediction of transportation energy demand by novel hybrid meta-heuristic ANN

MA Sahraei, MK Çodur - Energy, 2022 - Elsevier
Road automobiles are deemed one of the major resources of energy consumption
throughout cities. To realize and design sustainable urban transport, it is essential to …

Mitigating CO2 emissions in African transport networks under various policies and scenarios of Paris Agreement compliance

MI Shammas - International Journal of Sustainable Energy, 2024 - Taylor & Francis
This study analyzed the trajectory of CO2 emissions in the African transportation sector
under four different policy scenarios: no policy, low policy, the Paris Agreement with …

A review on the applicability of machine learning techniques to the metamodeling of energy systems

AR Starke, AK da Silva - Numerical Heat Transfer, Part B …, 2023 - Taylor & Francis
The use of physics-based models for the development and optimization of energy systems is
popular due to their versatility. However, their inherent complexity often makes these …

[HTML][HTML] Artificial intelligence and policy making; can small municipalities enable digital transformation?

I Koliousis, A Al-Surmi, M Bashiri - International Journal of Production …, 2024 - Elsevier
This study investigates digital transformation and the usability of emerging technologies in
policymaking. Prior studies categorised digital transformation into three distinct phases of …

How do machines predict energy use? Comparing machine learning approaches for modeling household energy demand in the United States

JW Burnett, LL Kiesling - Energy Research & Social Science, 2022 - Elsevier
This paper illustrates the use of different machine learning techniques to estimate household
energy demand. To demonstrate the performance of the techniques, we discuss how the …

Energy use forecasting with the use of a nested structure based on fuzzy cognitive maps and artificial neural networks

K Poczeta, EI Papageorgiou - Energies, 2022 - mdpi.com
The aim of this paper is to present a novel approach to energy use forecasting. We propose
a nested fuzzy cognitive map in which each concept at a higher level can be decomposed …

SA-LSTMs: A new advance prediction method of energy consumption in cement raw materials grinding system

G Liu, K Wang, X Hao, Z Zhang, Y Zhao, Q Xu - Energy, 2022 - Elsevier
Electricity consumption is a major energy efficiency indicator in cement raw materials
grinding system. Advance prediction of electricity consumption provides the basis for cement …

Assessing the factors affecting the perceived crossing speed of pedestrians and investigating the direct and indirect effects of crash risk perception on perceived …

A Saxena - Journal of Transport & Health, 2023 - Elsevier
Walking is the primary means of transportation. For assessing individual's health, travel
behaviour and benchmarking service levels of pedestrian infrastructure, walking/crossing …