How can artificial intelligence impact sustainability: A systematic literature review
AK Kar, SK Choudhary, VK Singh - Journal of Cleaner Production, 2022 - Elsevier
We need a proper mechanism to manage issues related to our environment, economy, and
society to proceed toward sustainability. Many researchers have worked for sustainable …
society to proceed toward sustainability. Many researchers have worked for sustainable …
[HTML][HTML] How can we manage biases in artificial intelligence systems–A systematic literature review
PS Varsha - International Journal of Information Management Data …, 2023 - Elsevier
Artificial intelligence is similar to human intelligence, and robots in organisations always
perform human tasks. However, AI encounters a variety of biases during its operational …
perform human tasks. However, AI encounters a variety of biases during its operational …
Decision making of autonomous vehicles in lane change scenarios: Deep reinforcement learning approaches with risk awareness
Driving safety is the most important element that needs to be considered for autonomous
vehicles (AVs). To ensure driving safety, we proposed a lane change decision-making …
vehicles (AVs). To ensure driving safety, we proposed a lane change decision-making …
A review of reinforcement learning based energy management systems for electrified powertrains: Progress, challenge, and potential solution
AH Ganesh, B Xu - Renewable and Sustainable Energy Reviews, 2022 - Elsevier
The impact of internal combustion engine-powered automobiles on climate change due to
emissions and the depletion of fossil fuels has contributed to the progress of electrified …
emissions and the depletion of fossil fuels has contributed to the progress of electrified …
Reinforcement learning and its applications in modern power and energy systems: A review
With the growing integration of distributed energy resources (DERs), flexible loads, and
other emerging technologies, there are increasing complexities and uncertainties for …
other emerging technologies, there are increasing complexities and uncertainties for …
Policy iteration reinforcement learning-based control using a grey wolf optimizer algorithm
This paper presents a new Reinforcement Learning (RL)-based control approach that uses
the Policy Iteration (PI) and a metaheuristic Grey Wolf Optimizer (GWO) algorithm to train the …
the Policy Iteration (PI) and a metaheuristic Grey Wolf Optimizer (GWO) algorithm to train the …
Reinforcement learning-based control using Q-learning and gravitational search algorithm with experimental validation on a nonlinear servo system
This paper presents a novel Reinforcement Learning (RL)-based control approach that uses
a combination of a Deep Q-Learning (DQL) algorithm and a metaheuristic Gravitational …
a combination of a Deep Q-Learning (DQL) algorithm and a metaheuristic Gravitational …
Deep reinforcement learning for power system applications: An overview
Due to increasing complexity, uncertainty and data dimensions in power systems,
conventional methods often meet bottlenecks when attempting to solve decision and control …
conventional methods often meet bottlenecks when attempting to solve decision and control …
Driving conditions-driven energy management strategies for hybrid electric vehicles: A review
Motivated by the concerns on transported fuel consumption and global air pollution,
industrial engineers and academic researchers have made many efforts to construct more …
industrial engineers and academic researchers have made many efforts to construct more …
Genetic algorithm optimized neural network based fuel cell hybrid electric vehicle energy management strategy under start-stop condition
D Min, Z Song, H Chen, T Wang, T Zhang - Applied Energy, 2022 - Elsevier
Because of its high efficiency, no emission, low noise and many other advantages, proton
exchange membrane fuel cell is considered to be able to be applied in automobiles to …
exchange membrane fuel cell is considered to be able to be applied in automobiles to …