Multisensor Data Fusion for Water Quality Evaluation Using Dempster-Shafer Evidence Theory
Joint Authors
Zhou, Jian
Guo, Jian
Sun, Lijuan
Liu, Linfeng
Source
International Journal of Distributed Sensor Networks
Issue
Vol. 2013, Issue - (31 Dec. 2013), pp.1-6, 6 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-11-14
Country of Publication
Egypt
No. of Pages
6
Main Subjects
Telecommunications Engineering
Information Technology and Computer Science
Abstract EN
A multisensor data fusion approach for water quality evaluation using Dempster-Shafer evidence theory is presented.
To evaluate water quality, each sensor measurement is considered as a piece of evidence.
Based on the water quality parameters measured by sensor node, the mass function of water quality class is calculated.
Evidence from each sensor is given a reliability discounting and then combined with the others by D-S rule.
According to the decision rule which uses the fusion mass function values, the class of water quality can be determined.
Finally, experiments are given to demonstrate that the proposed approach can evaluate water quality from uncertain sensor data and improve evaluation performance.
American Psychological Association (APA)
Zhou, Jian& Liu, Linfeng& Guo, Jian& Sun, Lijuan. 2013. Multisensor Data Fusion for Water Quality Evaluation Using Dempster-Shafer Evidence Theory. International Journal of Distributed Sensor Networks،Vol. 2013, no. -, pp.1-6.
https://search.emarefa.net/detail/BIM-449512
Modern Language Association (MLA)
Zhou, Jian…[et al.]. Multisensor Data Fusion for Water Quality Evaluation Using Dempster-Shafer Evidence Theory. International Journal of Distributed Sensor Networks Vol. 2013, pp.1-6.
https://search.emarefa.net/detail/BIM-449512
American Medical Association (AMA)
Zhou, Jian& Liu, Linfeng& Guo, Jian& Sun, Lijuan. Multisensor Data Fusion for Water Quality Evaluation Using Dempster-Shafer Evidence Theory. International Journal of Distributed Sensor Networks. 2013. Vol. 2013, no. -, pp.1-6.
https://search.emarefa.net/detail/BIM-449512
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-449512