Abstract
Electricity disaggregation focuses on classification of individual appliances by monitoring aggregate electrical signals. In this paper we present a novel algorithm to automatically correct labels, discard contaminated training samples, and boost signal to noise ratio through high frequency noise reduction. We also propose a method for prioritized classification which classifies appliances with the most intense signals first. When tested on four houses in Kaggles Belkin dataset, these methods automatically relabel over 77% of all training samples and decrease error rate by an average of 45% in both real power and high frequency noise classification.
| Original language | English (US) |
|---|---|
| Title of host publication | WS-16-01 |
| Subtitle of host publication | Artificial Intelligence Applied to Assistive Technologies and Smart Environments; WS-16-02: AI, Ethics, and Society; WS-16-03: Artificial Intelligence for Cyber Security; WS-16-04: Artificial Intelligence for Smart Grids and Smart Buildings; WS-16-05: Beyond NP; WS-16-06: Computer Poker and Imperfect Information Games; WS-16-07: Declarative Learning Based Programming; WS-16-08: Expanding the Boundaries of Health Informatics Using AI; WS-16-09: Incentives and Trust in Electronic Communities; WS-16-10: Knowledge Extraction from Text; WS-16-11: Multiagent Interaction without Prior Coordination; WS-16-12: Planning for Hybrid Systems; WS-16-13: Scholarly Big Data: AI Perspectives, Challenges, and Ideas; WS-16-14: Symbiotic Cognitive Systems; WS-16-15: World Wide Web and Population Health Intelligence |
| Publisher | AI Access Foundation |
| Pages | 262-269 |
| Number of pages | 8 |
| ISBN (Electronic) | 9781577357599 |
| State | Published - 2016 |
| Event | 30th AAAI Conference on Artificial Intelligence, AAAI 2016 - Phoenix, United States Duration: Feb 12 2016 → Feb 17 2016 |
Publication series
| Name | AAAI Workshop - Technical Report |
|---|---|
| Volume | WS-16-01 - WS-16-15 |
Other
| Other | 30th AAAI Conference on Artificial Intelligence, AAAI 2016 |
|---|---|
| Country/Territory | United States |
| City | Phoenix |
| Period | 2/12/16 → 2/17/16 |
Bibliographical note
Publisher Copyright:Copyright © 2016, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.
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