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University of Illinois at Urbana-Champaign

A machine learning pipeline for detecting anomalous energy usage in telecommunications sites

dc:creator Lee, Gregory

thesis:degree_name M.S.

dc:date2022

Abstract

dc:description

Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2023-04-12 without embargo terms

Degree

thesis:*

Name thesis:degree_name: M.S.
Level thesis:degree_level: Thesis
Discipline thesis:degree_discipline: Computer Science
Grantor: University of Illinois at Urbana-Champaign
Year dc:date: 2022

Author and committee

dc:creator, dc:contributor.*

Author dc:creator: Lee, Gregory
Contributors dc:contributor: Caesar, Matthew

Subjects

dc:subject × 3

Rights

dc:rights

Statement dc:rights: Copyright 2022 Gregory Lee
Language dc:language: en, eng

Identifiers

dc:identifier.*

Handle dc:identifier: https://hdl.handle.net/2142/117816
OAI identifier oai:identifier: oai:www.ideals.illinois.edu:2142/117816

Chain of custody

source

Harvested from: University of Illinois - Urbana-Champaign
Base URL: www.ideals.illinois.edu/oai-pmh
Last updated: 2026-07-22
Source record: OAI-PMH GetRecord

related terms

citation

Lee, Gregory. A machine learning pipeline for detecting anomalous energy usage in telecommunications sites. Thesis thesis, University of Illinois at Urbana-Champaign, 2022. https://hdl.handle.net/2142/117816

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