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