The DOI matches its Crossref record; 35 of the 35 references it cites were found in a registry or an index.
Fusing TensorFlow with building energy simulation for intelligent energy management in smart cities
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“It also involved using ML in empirical studies (e.g., Ref. [174,210]).”
From Smarter eco-cities and their leading-edge artificial intelligence of things solutions for environmental sustainability: A comprehensive systematic review (2024) · cites this paper as [210]
Citations
Cites
Reinforcement Learning: An Introduction
Sutton, R. S., & Barto, A. G. (1998) · IEEE Transactions on Neural Networks · doi:10.1109/tnn.1998.712192 · Cited by 27,225
Reinforcement Learning: An Introduction
Sutton, R. S., & Barto, A. (2005) · IEEE Transactions on Neural Networks · doi:10.1109/tnn.2004.842673 · Cited by 25,268
Watkins, C., & Dayan, P. (1992) · Machine-mediated learning · doi:10.1023/a:1022676722315 · Cited by 14,277
Playing Atari with Deep Reinforcement Learning
Mnih, V., Kavukcuoglu, K., Silver, D., Graves, A., Antonoglou, I., Wierstra, D., & Riedmiller, M. (2013) · arXiv · doi:10.48550/arxiv.1312.5602 · Cited by 9,471
TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems
Abadi, M., Agarwal, A., Barham, P., Brevdo, E., Chen, Z., Citro, C., Corrado, G. S., Davis, A., Dean, J., Devin, M., et al. (2016) · arXiv · doi:10.48550/arxiv.1603.04467 · Cited by 9,408
Watkins, C. J. C. H., & Dayan, P. (1992) · Machine Learning · doi:10.1007/bf00992698 · Cited by 9,083
Reinforcement Learning and Dynamic Programming Using Function Approximators
Buşoniu, L., Babuška, R., Schutter, B. D., & Ernst, D. (2010) · CRC Press eBooks · doi:10.1201/9781439821091 · Cited by 919
Reinforcement learning for demand response: A review of algorithms and modeling techniques
Vázquez-Canteli, J. R., & Nagy, Z. (2019) · Applied Energy · doi:10.1016/j.apenergy.2018.11.002 · Cited by 883
Self-citationOn-Line Building Energy Optimization Using Deep Reinforcement Learning
Mocanu, E., Mocanu, D. C., Nguyen, P. H., Liotta, A., Webber, M. E., Gibescu, M., & Slootweg, J. G. (2019) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2018.2834219 · Cited by 649
The Neural Network House: An Environment that Adapts to its Inhabitants
Mozer, M. C. (1998) · Cited by 500
Flagged first, then by citations
Research works printed but not linked: 3
- Javed, 2017, 4, 393
- Rault, 1978, 14, 413
- Vázquez-Canteli, 2016, Energy simulation at the urban scale: A focus on Geneva and climate change scenarios, Sustainable City, 204
Cited by
Sorted by citations
Artificial intelligence for sustainability: Challenges, opportunities, and a research agenda
Nishant, R., Kennedy, M., & Corbett, J. (2020) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2020.102104 · Cited by 1,203
Reinforcement learning for demand response: A review of algorithms and modeling techniques
Vázquez-Canteli, J. R., & Nagy, Z. (2019) · Applied Energy · doi:10.1016/j.apenergy.2018.11.002 · Cited by 883
Self-citationReinforcement learning for building controls: The opportunities and challenges
Wang, Z., & Hong, T. (2020) · Applied Energy · doi:10.1016/j.apenergy.2020.115036 · Cited by 590
Bibri, S. E., Krogstie, J., Kaboli, A., & Alahi, A. (2024) · Environmental Science and Ecotechnology · doi:10.1016/j.ese.2023.100330 · Cited by 536
Machine learning driven smart electric power systems: Current trends and new perspectives
Ibrahim, M. S., Dong, W., & Yang, Q. (2020) · Applied Energy · doi:10.1016/j.apenergy.2020.115237 · Cited by 462
Metadata
- Authors
- Vázquez-Canteli, J. R., Ulyanin, S., Kämpf, J., & Nagy, Z.
- Affiliations
- National Laboratory of the Rockies (US)
- Georgia Institute of Technology (US)
- Idiap Research Institute (CH)
- The University of Texas at Austin (US)
- Corresponding author
- Nagy, Zoltán
- Venue
- Sustainable Cities and Society
- Publisher
- Elsevier BV
- Published
- 2019-02
- Volume
- 45
- Pages
- 243-257
- ISSN
- 2210-6707 (ISSN-L)
- OpenAlex
- W2900981450
- Cited by
- 195
- References
- 33
- Citations by year
- 2026: 7 · 2025: 12 · 2024: 26 · 2023: 31 · 2022: 33 · 2021: 34 · 2020: 35 · 2019: 16
- FWCI
- 17.23
- Type
- journal article
- Language
- en
- Open access
- green
- infoscience.epfl.ch
- Licence
- cc-by-nc-nd
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- Locations
- Sustainable Cities and Society (publishedVersion)
- Infoscience (Ecole Polytechnique Fédérale de Lausanne) (submittedVersion, cc-by-nc-nd)
- Topics
- Physical Sciences › Engineering › Building and Construction › Building Energy and Comfort Optimization
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Smart Grid Energy Management
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Integrated Energy Systems Optimization
- Keywords
- building energy simulation, TensorFlow, Keras, CitySim, deep reinforcement learning, building energy management, demand response, energy conservation, smart cities, building energy standards
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