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Yueren Wang
Researcher at Microsoft
Publications - 4
Citations - 717
Yueren Wang is an academic researcher from Microsoft. The author has contributed to research in topics: Model building & Efficient energy use. The author has an hindex of 3, co-authored 3 publications receiving 371 citations. Previous affiliations of Yueren Wang include Guangzhou University.
Papers
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Random Forest based hourly building energy prediction
TL;DR: In this article, the authors proposed a homogeneous ensemble approach, i.e., use of Random Forest (RF), for hourly building energy prediction, which was adopted to predict the hourly electricity usage of two educational buildings in North Central Florida.
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Adopting Internet of Things for the development of smart buildings: A review of enabling technologies and applications
TL;DR: It is argued that a mature adoption of IoT technologies in the building industry is not yet realized and, therefore, calls for more attention from researchers in the relevant fields from the application perspective.
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A novel ensemble learning approach to support building energy use prediction
TL;DR: In this article, an ensemble bagging tree (EBT) was used to predict hourly electricity demand of the test building with improved accuracy of Mean Absolute Prediction Error that ranged from 2.97% to 4.63%.
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Machine learning approaches to determining truck type from bridge loading response
Yueren Wang,Ian Flood +1 more
TL;DR: In this paper , a review of existing methods of determining truck types and loading attributes using both machine learning and heuristic search techniques is provided, and the most promising approach to date, that of artificial neural networks, is then compared to support vector machines in a comprehensive study considering a range of configurations of both modeling techniques.