Deep Weighted Fusion Learning (DWFL)-based multi-sensor fusion model for accurate building occupancy detection

Author:

Rafi Md. Rumman,Hu FeiORCID,Li Shuhui,Song Aijun,Zhang Xingli,O’Neill Zheng

Funder

US Department of Energy

National Science Foundation

Advanced Research Projects Agency - Energy

Publisher

Elsevier BV

Reference19 articles.

1. Avaible online: https://www.energy.gov/eere/buildings/about-commercial-buildings-integration-program.

2. Hardware-based emulator with deep learning model for building energy control and prediction based on occupancy sensors’ data;Ye;Information,2021

3. Xue Hongfei, Jiang Wenjun, Miao Chenglin, Yuan Ye, Ma Fenglong, Ma Xin, Wang Yijiang, Yao Shuochao, Xu Wenyao, Zhang Aidong, et al. Deepfusion: A deep learning framework for the fusion of heterogeneous sensory data. In: Proceedings of the twentieth ACM international symposium on mobile ad hoc networking and computing. 2019, p. 151–60.

4. Machine learning based attack detection in internet of things network;Rafi;Int J Comput Sci Inf Secur,2021

5. Prediction of heart disease using data mining techniques: A case study;Shadid;Int J Res Publ,2019

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