Data-Driven Control of COVID-19 in Buildings: A Reinforcement-Learning Approach-Reference-Cited by-同舟云学术

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Data-Driven Control of COVID-19 in Buildings: A Reinforcement-Learning Approach

Published:2023 Issue: Volume: Page:1-0
ISSN:1545-5955
Container-title:IEEE Transactions on Automation Science and Engineering
language:
Short-container-title:IEEE Trans. Automat. Sci. Eng.

Author:

Hosseinloo Ashkan Haji¹^ORCID,Nabi Saleh²,Hosoi Anette³^ORCID,Dahleh Munther A.¹^ORCID

Affiliation:

1. Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA

2. Mitsubishi Electric Research Laboratories, Cambridge, MA, USA

3. Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA

Funder

NSF Modeling and Control of COVID-19 Transmission in Indoor Environments

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/8856/4358066/10265235.pdf?arnumber=10265235

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Ventilation and temperature control for energy-efficient and healthy buildings: A differentiable PDE approach;Applied Energy;2024-10

2. Robust Neural Differential Solution for Time-Dependent Nonlinear Optimization With Noises Rejection;IEEE Transactions on Automation Science and Engineering;2024

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