DocumentCode
514818
Title
Notice of Retraction
Improvement Research of Evidence Theory in Mine Water Inrush Prediction
Author
Xiao Jianyu ; Tong Minming ; Feng Wei ; Guo Xijin
Author_Institution
Sch. of Comput. Sci. & Technol., China Univ. of Min. & Technol., Xuzhou, China
Volume
1
fYear
2010
fDate
6-7 March 2010
Firstpage
260
Lastpage
263
Abstract
Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
Since the highly conflicting evidence could not be combined effectively through D-S evidence theory, a novel D-S data fusion method based on evidence quality is introduced in this paper. The concrete algorithm for the reliability of observer and the measure of quality function value based on observer reliability are proposed. In the data fusion, adopting the measure of evidence quality, the collected data from multi-sensor is assigned to the different weight according to the reliability of observer, and the probability assignment value is correspondingly adjusted. The improved D-S evidence theory, along with combining the highly conflicting evidence, is applied successfully to the prediction of mine water inrush. The experimental results show that the method is effective.
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
Since the highly conflicting evidence could not be combined effectively through D-S evidence theory, a novel D-S data fusion method based on evidence quality is introduced in this paper. The concrete algorithm for the reliability of observer and the measure of quality function value based on observer reliability are proposed. In the data fusion, adopting the measure of evidence quality, the collected data from multi-sensor is assigned to the different weight according to the reliability of observer, and the probability assignment value is correspondingly adjusted. The improved D-S evidence theory, along with combining the highly conflicting evidence, is applied successfully to the prediction of mine water inrush. The experimental results show that the method is effective.
Keywords
case-based reasoning; forecasting theory; mining; probability; quality function deployment; reliability theory; sensor fusion; water; D-S data fusion; D-S evidence theory; evidence quality; improvement research; mine water inrush prediction; observer reliability; probability assignment value; quality function value; Computer science; Computer science education; Concrete; Educational institutions; Educational technology; Fuel processing industries; Information analysis; Reliability theory; Surges; Uncertainty; D-S evidence theory; observer reliability; quality function; water inrush prediction;
fLanguage
English
Publisher
ieee
Conference_Titel
Education Technology and Computer Science (ETCS), 2010 Second International Workshop on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-6388-6
Type
conf
DOI
10.1109/ETCS.2010.379
Filename
5459135
Link To Document