The DOI matches its Crossref record.
A Data Driven Approach for Smart Lighting
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“In the same year, Guo et al. [23] applies machine learning to smart lighting, namely AdaBoost learning on sensor data for intelligent control.”
From Machine Learning Methods in Smart Lighting Toward Achieving User Comfort: A Survey (2022) · cites this paper as [23]
Citations
Cites
No references could be resolved yet.
Research works printed but not linked: 10
- Duda, R., Hart, P., Stork, D.: Pattern Classification. Wiley-Interscience (2000)
- Freund, Y., Schapire, R.E.: Experiments with a new boosting algorithm. In: ICML 1996, pp. 148–156 (1996)
- Gu, Y.: The Impacts of Real-time Knowledge Based Personal Lighting Control on Energy Consumption, User Satisfaction and Task Performance in Offices. PhD thesis, Carnegie Mellon University (2011)
- Guo, H., Létourneau, S.: Iterative classification for multiple target attributes. J. Intell. Inf. Syst. 40(2), 283–305 (2013) · DOI
- Mitchell, M.T.: Machine Learning. McGraw Hill, New York (1996)
- Neville, J., Jensen, D.: Iterative classification in relational data. In: AAAI Workshop on Learning Statistical Models from Relational Data, 13-20 (2000)
- Opitz, D., Maclin, R.: Popular ensemble methods: An empirical study. Journal of Artificial Intelligence Research 11, 169–198 (1999) · DOI · Paper page
- Quinlan, J.R.: C4.5: programs for machine learning. Morgan Kaufmann Publishers Inc., USA (1993)
- Wen, Y.-J., Agogino, A.: Control of wireless-networked lighting in open-plan offices. Lighting Research and Technology 43, 235–248 (2011) · DOI
- Wen, Y.-J., Bonnell, J., Agogino, A.M.: Energy conservation utilizing wireless dimmable lighting control in a shared-space office. In: Proceedings of the 2008 Annual Conference of the Illuminating Engineering Society (2008)
Cited by
Sorted by citations
Machine Learning Methods in Smart Lighting Toward Achieving User Comfort: A Survey
Putrada, A. G., Abdurohman, M., Perdana, D., & Nuha, H. H. (2022) · IEEE Access · doi:10.1109/access.2022.3169765 · Cited by 101
“In the same year, Guo et al. [23] applies machine learning to smart lighting, namely AdaBoost learning on sensor data for intelligent control.”
Background
Metadata
- Authors
- Guo, H., Letourneau, S., & Yang, C.
- Affiliations
- National Research Council Canada (CA)
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer International Publishing
- Published
- 2014
- Pages
- 308-317
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W305579182
- Cited by
- 2
- References
- 0
- Citations by year
- 2026: 1 · 2022: 1
- FWCI
- 0.00
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- Lecture notes in computer science (publishedVersion)
- NPARC (submittedVersion)
- Topics
- Physical Sciences › Engineering › Building and Construction › Building Energy and Comfort Optimization
- Physical Sciences › Engineering › Architecture › Facilities and Workplace Management
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Keywords
- smart lighting, lighting comfort, collective classification, lighting control strategies
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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