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Identifying Metering Hierarchies with Distance Correlation and Dominance Constraints

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Identifying Metering Hierarchies with Distance Correlation and Dominance Constraints. / Chan, Tak-Shing; Gibberd, Alex.
Proceedings - 21st IEEE International Conference on Machine Learning and Applications, ICMLA 2022. ed. / M. Arif Wani; Mehmed Kantardzic; Vasile Palade; Daniel Neagu; Longzhi Yang; Kit-Yan Chan. IEEE, 2023. p. 1551-1558 (2022 21st IEEE International Conference on Machine Learning and Applications (ICMLA)).

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

Harvard

Chan, T-S & Gibberd, A 2023, Identifying Metering Hierarchies with Distance Correlation and Dominance Constraints. in MA Wani, M Kantardzic, V Palade, D Neagu, L Yang & K-Y Chan (eds), Proceedings - 21st IEEE International Conference on Machine Learning and Applications, ICMLA 2022. 2022 21st IEEE International Conference on Machine Learning and Applications (ICMLA), IEEE, pp. 1551-1558, 2022 21st IEEE International Conference on Machine Learning and Applications, Nassau, Bahamas, 12/12/22. https://doi.org/10.1109/ICMLA55696.2022.00242

APA

Chan, T-S., & Gibberd, A. (2023). Identifying Metering Hierarchies with Distance Correlation and Dominance Constraints. In M. A. Wani, M. Kantardzic, V. Palade, D. Neagu, L. Yang, & K-Y. Chan (Eds.), Proceedings - 21st IEEE International Conference on Machine Learning and Applications, ICMLA 2022 (pp. 1551-1558). (2022 21st IEEE International Conference on Machine Learning and Applications (ICMLA)). IEEE. https://doi.org/10.1109/ICMLA55696.2022.00242

Vancouver

Chan T-S, Gibberd A. Identifying Metering Hierarchies with Distance Correlation and Dominance Constraints. In Wani MA, Kantardzic M, Palade V, Neagu D, Yang L, Chan K-Y, editors, Proceedings - 21st IEEE International Conference on Machine Learning and Applications, ICMLA 2022. IEEE. 2023. p. 1551-1558. (2022 21st IEEE International Conference on Machine Learning and Applications (ICMLA)). doi: 10.1109/ICMLA55696.2022.00242

Author

Chan, Tak-Shing ; Gibberd, Alex. / Identifying Metering Hierarchies with Distance Correlation and Dominance Constraints. Proceedings - 21st IEEE International Conference on Machine Learning and Applications, ICMLA 2022. editor / M. Arif Wani ; Mehmed Kantardzic ; Vasile Palade ; Daniel Neagu ; Longzhi Yang ; Kit-Yan Chan. IEEE, 2023. pp. 1551-1558 (2022 21st IEEE International Conference on Machine Learning and Applications (ICMLA)).

Bibtex

@inproceedings{4e8d03244b994b36a1a74391a82f28f0,
title = "Identifying Metering Hierarchies with Distance Correlation and Dominance Constraints",
abstract = "In this paper, we consider observations from a series of smart meters that are either completely or partially aggregated, and our aim is to estimate the metering hierarchy. We propose to estimate this important metadata through a novel adaptation of the Chow–Liu tree learning procedure. Our approach takes into account prior knowledge from a set of dominance conditions that are easily elicited from the consumption data. In addition to more traditional correlation-based approaches we also introduce a distance-correlation-based method for detecting edges. Synthetic experiments show the benefits of distance correlation and the dominance conditions in recovering tree structure. The paper concludes with a real-world application of the method to infer energy metering hierarchies in a library building.",
keywords = "smart meter, metadata, spanning trees and arborescences, distance correlation, aggregation",
author = "Tak-Shing Chan and Alex Gibberd",
year = "2023",
month = mar,
day = "23",
doi = "10.1109/ICMLA55696.2022.00242",
language = "English",
isbn = "9781665462846",
series = "2022 21st IEEE International Conference on Machine Learning and Applications (ICMLA)",
publisher = "IEEE",
pages = "1551--1558",
editor = "Wani, {M. Arif} and Mehmed Kantardzic and Vasile Palade and Daniel Neagu and Longzhi Yang and Kit-Yan Chan",
booktitle = "Proceedings - 21st IEEE International Conference on Machine Learning and Applications, ICMLA 2022",
note = "2022 21st IEEE International Conference on Machine Learning and Applications, ICMLA 2022 ; Conference date: 12-12-2022 Through 14-12-2022",
url = "https://www.icmla-conference.org/icmla22/",

}

RIS

TY - GEN

T1 - Identifying Metering Hierarchies with Distance Correlation and Dominance Constraints

AU - Chan, Tak-Shing

AU - Gibberd, Alex

PY - 2023/3/23

Y1 - 2023/3/23

N2 - In this paper, we consider observations from a series of smart meters that are either completely or partially aggregated, and our aim is to estimate the metering hierarchy. We propose to estimate this important metadata through a novel adaptation of the Chow–Liu tree learning procedure. Our approach takes into account prior knowledge from a set of dominance conditions that are easily elicited from the consumption data. In addition to more traditional correlation-based approaches we also introduce a distance-correlation-based method for detecting edges. Synthetic experiments show the benefits of distance correlation and the dominance conditions in recovering tree structure. The paper concludes with a real-world application of the method to infer energy metering hierarchies in a library building.

AB - In this paper, we consider observations from a series of smart meters that are either completely or partially aggregated, and our aim is to estimate the metering hierarchy. We propose to estimate this important metadata through a novel adaptation of the Chow–Liu tree learning procedure. Our approach takes into account prior knowledge from a set of dominance conditions that are easily elicited from the consumption data. In addition to more traditional correlation-based approaches we also introduce a distance-correlation-based method for detecting edges. Synthetic experiments show the benefits of distance correlation and the dominance conditions in recovering tree structure. The paper concludes with a real-world application of the method to infer energy metering hierarchies in a library building.

KW - smart meter

KW - metadata

KW - spanning trees and arborescences

KW - distance correlation

KW - aggregation

U2 - 10.1109/ICMLA55696.2022.00242

DO - 10.1109/ICMLA55696.2022.00242

M3 - Conference contribution/Paper

SN - 9781665462846

T3 - 2022 21st IEEE International Conference on Machine Learning and Applications (ICMLA)

SP - 1551

EP - 1558

BT - Proceedings - 21st IEEE International Conference on Machine Learning and Applications, ICMLA 2022

A2 - Wani, M. Arif

A2 - Kantardzic, Mehmed

A2 - Palade, Vasile

A2 - Neagu, Daniel

A2 - Yang, Longzhi

A2 - Chan, Kit-Yan

PB - IEEE

T2 - 2022 21st IEEE International Conference on Machine Learning and Applications

Y2 - 12 December 2022 through 14 December 2022

ER -