Results 181 to 190 of about 16,083 (234)
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2018 North American Power Symposium (NAPS), 2018
A distributed energy management system for an interconnected multi-microgrid system is developed and tested. The distributed energy management system is formulated using the alternating direction method of multipliers (ADMM) and is implemented using the CVX platform of the MATLAB environment.
Shravan Kumar Akula, Hossein Salehfar
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A distributed energy management system for an interconnected multi-microgrid system is developed and tested. The distributed energy management system is formulated using the alternating direction method of multipliers (ADMM) and is implemented using the CVX platform of the MATLAB environment.
Shravan Kumar Akula, Hossein Salehfar
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Relaxing Alternating Direction Method of Multipliers (ADMM) for Linear Inverse Problems
2018We investigate the Alternating Direction Method of Multipliers (ADMM) for solving linear inverse problems. In particular, a relaxing factor is introduced to the standard algorithm allowing more flexible updating of the Lagrange multiplier. The convergence result is established for the Relaxing ADMM for the noise free data under appropriate assumptions.
Zehui Wu, Shuai Lu
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2024 6th International Academic Exchange Conference on Science and Technology Innovation (IAECST)
In this paper, we propose a signal detection algorithm based on ADMM and channel sparsity, with the aim of achieving an optimal balance between the performance and complexity of MIMO-SCMA systems.
Yangsen Fu +3 more
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In this paper, we propose a signal detection algorithm based on ADMM and channel sparsity, with the aim of achieving an optimal balance between the performance and complexity of MIMO-SCMA systems.
Yangsen Fu +3 more
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International Journal of Hydrogen Energy, 2021
In this paper, a method based on alternating direction method of multipliers (ADMM) algorithm is proposed to solve the energy management problem for fuel cell vehicles (FCVs).
Xiaodong Wei, Chao Sun, Weiwei Huo
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In this paper, a method based on alternating direction method of multipliers (ADMM) algorithm is proposed to solve the energy management problem for fuel cell vehicles (FCVs).
Xiaodong Wei, Chao Sun, Weiwei Huo
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IEEE transactions on industry applications, 2023
This paper proposes a fully decentralized distributed convex optimal power flow model for inverter-based distributed energy resources (DERs) integrated electric distribution networks based on Semi-Definite Programming (SDP) and alternating direction ...
B. Biswas +2 more
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This paper proposes a fully decentralized distributed convex optimal power flow model for inverter-based distributed energy resources (DERs) integrated electric distribution networks based on Semi-Definite Programming (SDP) and alternating direction ...
B. Biswas +2 more
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IEEE Transactions on Neural Networks and Learning Systems, 2021
Large-scale undirected weighted networks are frequently encountered in big-data-related applications concerning interactions among a large unique set of entities.
Xin Luo +3 more
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Large-scale undirected weighted networks are frequently encountered in big-data-related applications concerning interactions among a large unique set of entities.
Xin Luo +3 more
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Journal of Optimization Theory and Applications, 2023
To ensure the system stability of the H2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt ...
Bo Yang +3 more
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To ensure the system stability of the H2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt ...
Bo Yang +3 more
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IEEE Transactions on Image Processing, 2023
One-class classification aims to learn one-class models from only in-class training samples. Because of lacking out-of-class samples during training, most conventional deep learning based methods suffer from the feature collapse problem. In contrast, contrastive learning based methods can learn features from only in-class samples but are hard to be end-
Chien-Yu Chiou +3 more
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One-class classification aims to learn one-class models from only in-class training samples. Because of lacking out-of-class samples during training, most conventional deep learning based methods suffer from the feature collapse problem. In contrast, contrastive learning based methods can learn features from only in-class samples but are hard to be end-
Chien-Yu Chiou +3 more
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Journal of Renewable and Sustainable Energy, 2023
The superiorities of renewable energy, such as wind and solar energy, have promoted the development of microgrids (MGs) and multi-microgrids (MMGs).
Zhenlei Li +3 more
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The superiorities of renewable energy, such as wind and solar energy, have promoted the development of microgrids (MGs) and multi-microgrids (MMGs).
Zhenlei Li +3 more
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2020 57th ACM/IEEE Design Automation Conference (DAC), 2020
This paper presents a novel timing driven global placement approach utilizing the alternating direction method of multipliers (ADMM) targeting superconductive electronic circuits. The proposed algorithm models the placement problem as an optimization problem with constraints on the maximum wirelength delay of timing-critical paths and employs the ADMM ...
Soheil Nazar Shahsavani, Massoud Pedram
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This paper presents a novel timing driven global placement approach utilizing the alternating direction method of multipliers (ADMM) targeting superconductive electronic circuits. The proposed algorithm models the placement problem as an optimization problem with constraints on the maximum wirelength delay of timing-critical paths and employs the ADMM ...
Soheil Nazar Shahsavani, Massoud Pedram
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