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Towards an approach to multivariate outlier detection for District Heating System data — arXiv:2608.11375

Source: arXiv (en)
Original: https://arxiv.org/abs/2608.11375
License (as archived): CC0-1.0
Archived: 2026-10-19T05:39:42.899Z
SHA-256 of the archived text: 9cce2c7408184a1bfa638cf7b8506400dedd35ecc87cc04f957518759ebdf975
Stable URL of this page: https://metraipolis.com/documento/dc_39d192c8a22d

How to cite

Towards an approach to multivariate outlier detection for District Heating System data — arXiv:2608.11375 — arXiv (en), https://arxiv.org/abs/2608.11375 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_39d192c8a22d (Metraipolis archive dc_39d192c8a22d, sha256 9cce2c7408184a1bfa638cf7b8506400dedd35ecc87cc04f957518759ebdf975)

BibTeX

@misc{dc39d192c8a22d,
  title = {Towards an approach to multivariate outlier detection for District Heating System data — arXiv:2608.11375},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2608.11375},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_39d192c8a22d; sha256 9cce2c7408184a1bfa638cf7b8506400dedd35ecc87cc04f957518759ebdf975},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2608.11375. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

In this paper, we test different methods for multivariate detection of outliers in the data of transmitted heat energy in the selected substation of local District Heating System, by also considering outside ambient temperature, namely Z-score (univariate, as a benchmark), Mahalanobis distances, Principal Component Analysis (PCA), Isolation Forest and Hotelling's T-squared test. The overall research aims at uncovering irregular plant operation, with a wider objective of identifying the opportunities for reducing the consumption of gas in central heating plants as well as the CO2 emission. The proposed approach considers specific domain circumstances, such as irrelevance of zero transmit-ted energy timepoints as indication of off-grid plant. The outcomes of the different methods are discussed with domain experts. It was concluded that PCA, Isolation Forest and Hotelling method provide relevant results. Finally, we adopt the ensemble method (selection based on the agreement of all three methods on the detected outliers) as the final approach.

Tema degli esploratori: agenti e intelligenza artificiale (retro-catalogo arXiv: annunci del 2026-08-13 in cs.LG).
Categorie arXiv: Machine Learning (cs.LG) ; Systems and Control (eess.SY).
Pagina del lavoro: https://arxiv.org/abs/2608.11375 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-19T05:18:32.459Z dalla pagina https://arxiv.org/catchup/cs.LG/2026-08-13?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).