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Article

A Possible World-Based Fusion Estimation Model for Uncertain Data Clustering in WBNs

1
Department of Electronic and Information Engineering, Key Laboratory of Communication and Information Systems, Beijing Municipal Commission of Education, Beijing Jiaotong University, Beijing 100044, China
2
The School of Software Engineering, Beijing Jiaotong University, Beijing 100044, China
3
Shaanxi Key Laboratory for Network Computing and Security Technology, School of Computer Science and Engineering, Xi’an University of Technology, Xi’an 710048, China
4
Department of Electrical Engineering, National Dong Hwa University, Hualien 97401, Taiwan
5
School of Information Engineering, Beijing Institute of Petrochemical Technology, Beijing 102617, China
*
Author to whom correspondence should be addressed.
Academic Editor: Dawid Połap
Sensors 2021, 21(3), 875; https://doi.org/10.3390/s21030875
Received: 15 December 2020 / Revised: 24 January 2021 / Accepted: 25 January 2021 / Published: 28 January 2021
In data clustering, the measured data are usually regarded as uncertain data. As a probability-based clustering technique, possible world can easily cluster the uncertain data. However, the method of possible world needs to satisfy two conditions: determine the data of different possible worlds and determine the corresponding probability of occurrence. The existing methods mostly make multiple measurements and treat each measurement as deterministic data of a possible world. In this paper, a possible world-based fusion estimation model is proposed, which changes the deterministic data into probability distribution according to the estimation algorithm, and the corresponding probability can be confirmed naturally. Further, in the clustering stage, the Kullback–Leibler divergence is introduced to describe the relationships of probability distributions among different possible worlds. Then, an application in wearable body networks (WBNs) is given, and some interesting conclusions are shown. Finally, simulations show better performance when the relationships between features in measured data are more complex. View Full-Text
Keywords: possible worlds; fusion estimation; uncertain data; clustering possible worlds; fusion estimation; uncertain data; clustering
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MDPI and ACS Style

Li, C.; Zhang, Z.; Wei, W.; Chao, H.-C.; Liu, X. A Possible World-Based Fusion Estimation Model for Uncertain Data Clustering in WBNs. Sensors 2021, 21, 875. https://doi.org/10.3390/s21030875

AMA Style

Li C, Zhang Z, Wei W, Chao H-C, Liu X. A Possible World-Based Fusion Estimation Model for Uncertain Data Clustering in WBNs. Sensors. 2021; 21(3):875. https://doi.org/10.3390/s21030875

Chicago/Turabian Style

Li, Chao, Zhenjiang Zhang, Wei Wei, Han-Chieh Chao, and Xuejun Liu. 2021. "A Possible World-Based Fusion Estimation Model for Uncertain Data Clustering in WBNs" Sensors 21, no. 3: 875. https://doi.org/10.3390/s21030875

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