Towards Predicting the Perceived Brightness in a Smart Home Through Symbolic Regression-Reference-Cited by-同舟云学术

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Towards Predicting the Perceived Brightness in a Smart Home Through Symbolic Regression

Published:2024-03-11 Issue: Volume: Page:457-460
ISSN:
Container-title:2024 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops)
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Author:

Zdankin Peter¹,Matkovic Viktor¹,Schiele Gregor¹,Weis Torben¹

Affiliation:

1. University of Duisburg-Essen,Germany

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10502396/10502378/10502697.pdf?arnumber=10502697

Reference10 articles.

1. Smart home-worldwide,2023

2. The global smart home market size was valued at $80.21 billion in 2022 & is projected to grow from $93.98 billion in 2023 to $338.28 billion by 2030;Insights,2023

3. Interpretable machine learning for science with pysr and symbolicregression.jl;Cranmer,2023

4. AI Feynman: A physics-inspired method for symbolic regression

5. gplearn website;Stephens,2022

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