Sensors 2010, 10(10), 9384-9396; doi:10.3390/s101009384
Article

Sensor Data Fusion for Accurate Cloud Presence Prediction Using Dempster-Shafer Evidence Theory

1,* email, 2email and 2email
Received: 30 August 2010; in revised form: 15 September 2010 / Accepted: 25 September 2010 / Published: 18 October 2010
(This article belongs to the Special Issue Intelligent Sensors - 2010)
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract: Sensor data fusion technology can be used to best extract useful information from multiple sensor observations. It has been widely applied in various applications such as target tracking, surveillance, robot navigation, signal and image processing. This paper introduces a novel data fusion approach in a multiple radiation sensor environment using Dempster-Shafer evidence theory. The methodology is used to predict cloud presence based on the inputs of radiation sensors. Different radiation data have been used for the cloud prediction. The potential application areas of the algorithm include renewable power for virtual power station where the prediction of cloud presence is the most challenging issue for its photovoltaic output. The algorithm is validated by comparing the predicted cloud presence with the corresponding sunshine occurrence data that were recorded as the benchmark. Our experiments have indicated that comparing to the approaches using individual sensors, the proposed data fusion approach can increase correct rate of cloud prediction by ten percent, and decrease unknown rate of cloud prediction by twenty three percent.
Keywords: multi-sensor; data fusion; dempster-shafer; prediction; renewable energy; virtual power station
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MDPI and ACS Style

Li, J.; Luo, S.; Jin, J.S. Sensor Data Fusion for Accurate Cloud Presence Prediction Using Dempster-Shafer Evidence Theory. Sensors 2010, 10, 9384-9396.

AMA Style

Li J, Luo S, Jin JS. Sensor Data Fusion for Accurate Cloud Presence Prediction Using Dempster-Shafer Evidence Theory. Sensors. 2010; 10(10):9384-9396.

Chicago/Turabian Style

Li, Jiaming; Luo, Suhuai; Jin, Jesse S. 2010. "Sensor Data Fusion for Accurate Cloud Presence Prediction Using Dempster-Shafer Evidence Theory." Sensors 10, no. 10: 9384-9396.

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