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Brandon Foggo
Brandon Foggo
Postdoctoral Researcher at the University of California, Riverside
在 ucr.edu 的电子邮件经过验证
标题
引用次数
引用次数
年份
Phase identification in electric power distribution systems by clustering of smart meter data
W Wang, N Yu, B Foggo, J Davis, J Li
2016 15th IEEE International Conference on Machine Learning and Applications …, 2016
1152016
A physically inspired data-driven model for electricity theft detection with smart meter data
Y Gao, B Foggo, N Yu
IEEE Transactions on Industrial Informatics 15 (9), 5076-5088, 2019
1022019
Stochastic valuation of energy storage in wholesale power markets
N Yu, B Foggo
Energy Economics 64, 177-185, 2017
752017
Improved battery storage valuation through degradation reduction
B Foggo, N Yu
IEEE Transactions on Smart Grid 9 (6), 5721-5732, 2017
692017
Power system event identification based on deep neural network with information loading
J Shi, B Foggo, N Yu
IEEE Transactions on Power Systems 36 (6), 5622-5632, 2021
532021
GaSb thermophotovoltaic cells grown on GaAs by molecular beam epitaxy using interfacial misfit arrays
BC Juang, RB Laghumavarapu, BJ Foggo, PJ Simmonds, A Lin, B Liang, ...
Applied Physics Letters 106 (11), 2015
522015
Improving supervised phase identification through the theory of information losses
B Foggo, N Yu
IEEE Transactions on Smart Grid 11 (3), 2337-2346, 2019
452019
Data driven predictive maintenance of distribution transformers
F Kabir, B Foggo, N Yu
2018 China international conference on electricity distribution (CICED), 312-316, 2018
412018
A comprehensive evaluation of supervised machine learning for the phase identification problem
B Foggo, N Yu
International Journal of Computer and Systems Engineering 12 (6), 419-427, 2018
332018
Online event detection in synchrophasor data with graph signal processing
J Shi, B Foggo, X Kong, Y Cheng, N Yu, K Yamashita
2020 IEEE International conference on communications, control, and computing …, 2020
282020
Online power system event detection via bidirectional generative adversarial networks
Y Cheng, N Yu, B Foggo, K Yamashita
IEEE Transactions on Power Systems 37 (6), 4807-4818, 2022
222022
Online PMU missing value replacement via event-participation decomposition
B Foggo, N Yu
IEEE Transactions on Power Systems 37 (1), 488-496, 2021
172021
Dynamic parameter estimation with physics-based neural ordinary differential equations
X Kong, K Yamashita, B Foggo, N Yu
2022 IEEE Power & Energy Society General Meeting (PESGM), 1-5, 2022
92022
Information losses in neural classifiers from sampling
B Foggo, N Yu, J Shi, Y Gao
IEEE transactions on neural networks and learning systems 31 (10), 4073-4083, 2019
8*2019
Online voltage event detection using synchrophasor data with structured sparsity-inducing norms
X Kong, B Foggo, K Yamashita, N Yu
IEEE Transactions on Power Systems 37 (5), 3506-3515, 2021
62021
On the maximum mutual information capacity of neural architectures
B Foggo, N Yu
arXiv preprint arXiv:2006.06037, 2020
62020
pmuBAGE: The benchmarking assortment of generated PMU data for power system events
B Foggo, K Yamashita, N Yu
IEEE Transactions on Power Systems 39 (2), 3485-3496, 2023
52023
Missing value replacement for pmu data via deep learning model with magnitude trend decoupling
Y Cheng, B Foggo, K Yamashita, N Yu
IEEE Access 11, 27450-27461, 2023
42023
pmuBAGE: The Benchmarking Assortment of Generated PMU Data for Power System Events--Part I: Overview and Results
B Foggo, K Yamashita, N Yu
arXiv preprint arXiv:2204.01095, 2022
32022
A Dynamic Behavior-Based Bulk Power System Event Signature Library With Empirical Clustering
K Yamashita, B Foggo, X Kong, Y Cheng, J Shi, N Yu
IEEE Access 10, 96307-96321, 2022
22022
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