Machine learning and deep learning in energy systems: A review
With population increases and a vital need for energy, energy systems play an important
and decisive role in all of the sectors of society. To accelerate the process and improve the …
and decisive role in all of the sectors of society. To accelerate the process and improve the …
[HTML][HTML] Review of optimal sizing and power management strategies for fuel cell/battery/super capacitor hybrid electric vehicles
Energy management strategies and optimal power source sizing for fuel cell/battery/super
capacitor hybrid electric vehicles (HEVs) are critical for power splitting and cost-effective …
capacitor hybrid electric vehicles (HEVs) are critical for power splitting and cost-effective …
Efficient experimental energy management operating for FC/battery/SC vehicles via hybrid Artificial Neural Networks-Passivity Based Control
Nowadays, the energy management of multisource hybrid systems is becoming an
interesting and challenging topic for many researchers. The judicious choice of the energy …
interesting and challenging topic for many researchers. The judicious choice of the energy …
Carbon emission prediction of 275 cities in China considering artificial intelligence effects and feature interaction: A heterogeneous deep learning modeling …
High technology and artificial intelligence (AI) are crucial for achieving urban Dual Carbon
Goals. This study proposes a heterogeneous deep learning framework with analysis and …
Goals. This study proposes a heterogeneous deep learning framework with analysis and …
Planning and operation objectives of public electric vehicle charging infrastructures: A review
V Anadón Martínez, A Sumper - Energies, 2023 - mdpi.com
Planning public electric vehicle (EV) charging infrastructure has gradually become a key
factor in the electrification of mobility and decarbonization of the transport sector. In order to …
factor in the electrification of mobility and decarbonization of the transport sector. In order to …
A novel data-driven decision model based on extended belief rule base to predict China's carbon emissions
Global warming and climate change are gaining traction in recent years. As a major cause of
global warming, carbon emissions were centered to China's climate change policy …
global warming, carbon emissions were centered to China's climate change policy …
[HTML][HTML] A multivariable output neural network approach for simulation of plug-in hybrid electric vehicle fuel consumption
BP Adedeji - Green Energy and Intelligent Transportation, 2023 - Elsevier
This study is laser focused on the simulation of fuel consumption and fuel economy label
parameters of plug-in hybrid electric vehicles. While fuel economy is a key factor in the …
parameters of plug-in hybrid electric vehicles. While fuel economy is a key factor in the …
Enhancing CO2 emissions prediction in Africa: A novel approach integrating enviroeconomic factors and nature-inspired neural network in the presence of unit root
The prediction of CO 2 emissions is critical for designing sustainable environmental policies
and meeting the Sustainable Development Goals, particularly those related to climate …
and meeting the Sustainable Development Goals, particularly those related to climate …
A review of applications of artificial intelligence in heavy duty trucks
Due to the increasing use of automobiles, the transportation industry is facing challenges of
increased emissions, driver safety concerns, travel demand, etc. Hence, automotive …
increased emissions, driver safety concerns, travel demand, etc. Hence, automotive …
A data-driven rule-base approach for carbon emission trend forecast with environmental regulation and efficiency improvement
Greenhouse gas emissions are widely recognized as the primary cause of global warming,
leading to a growing attention on carbon emission management. However, the existing …
leading to a growing attention on carbon emission management. However, the existing …