Abstract: Remaining useful life (RUL) prediction of lithium-ion batteries can assess the battery reliability to determine the advent of failure and mitigate battery risk. The existing RUL prediction ...
Abstract: The Universal Verification Methodology (UVM) that can improve interoperability, reduce the cost of using intellectual property (IP) for new projects or electronic design automation (EDA) ...
Abstract: This paper compares applications of scenario-based and interval optimization approaches to stochastic security-constrained unit commitment (Stochastic SCUC). The uncertainty of wind power ...
Abstract: This paper proposes a methodology to increase the lifetime of the central battery energy storage system (CBESS) in an islanded building-level DC microgrid (MG) and enhance the voltage ...
Abstract: Mobile edge computing has risen as a promising technology for augmenting the computational capabilities of mobile devices. Meanwhile, in-network caching has become a natural trend of the ...
Abstract: This paper deals with the transient stability of a grid-forming converter while embedding a current reference saturation strategy. The novelty of this work consists in investigating the ...
Abstract: Battery storage is usually employed in photovoltaic (PV) system to mitigate the power fluctuations due to the characteristics of PV panels and solar irradiance. Control schemes for ...
Abstract: Symmetry is ubiquitous in nature, physics, and mathematics. However, a classical symmetry-agnostic reinforcement learning (RL) approach cannot guarantee to respect symmetry. Researchers have ...
Abstract: In this paper, robust adaptive neural network (NN) control is investigated for a general class of uncertain multiple-input-multiple-output (MIMO) nonlinear systems with unknown control ...
Abstract: This paper presents robust virtual inertia control of an islanded microgrid considering high penetration of renewable energy sources (RESs). In such microgrids, the lack of system inertia ...
Abstract: In this article, we propose a new pan-sharpening method that disentangles low spatial resolution multispectral (LRMS) and panchromatic (PAN) images in terms of sensor-specific features and ...
Abstract: For hyperspectral image (HSI) classification, two branch networks generally use convolutional neural networks (CNNs) to extract the spatial features and long short-term memory (LSTM) to ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results