Abstract: We introduce an optimization assisted by a neural network (ONN) predictor to the electromagnetic community. ONN belongs to the class of the surrogate model-based optimization approaches, and ...
Given that extreme weather disturbances frequently threaten the safe and stable operation of new power systems, the uncertainty of source–load forecasting has become a particular bottleneck affecting ...
Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. This research introduces a machine learning-centric approach to replicate olfactory ...
Abstract: This paper presents the hierarchical Q-learning path planning (HQPP) architecture for solving the cooperative tracking control problem of multi-agent systems (MASs) with lumped uncertainties ...
Welcome to piglot, a Python tool taylored for the automated optimisation of responses from numerical solvers. We aim to provide a simple and user-friendly interface that is also easily extendable, ...
Faculty of Engineering Sciences, Kyushu University, Kasuga, Fukuoka 816-8580, Japan Article Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) ...
The uncertainty of renewable energy and demand response brings many challenges to the microgrid energy management. Driven by the recent advances and applications of deep reinforcement learning a ...
The current release of this book can be found at here. This book was desigend originally for the undergraduete course ISE 3434 - "Deterministic Operations Research II" taught at Virginia Tech. I will ...
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