DocumentCode
3592881
Title
Notice of Retraction
Study of mine dust density sensor output characteristic----based on normal linear regression method of Excel
Author
Cheng Xuezhen ; Yang Fen ; Cao Maoyong
Author_Institution
Coll. of Inf. & Electr. Eng., Shandong Univ. of Sci. & Technol., Qingdao, China
Volume
8
fYear
2010
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.
By normal linear regression method of Excel, this article1 carries out normal distribution curve fitting with data collection of mine dust density sensor. The experimented data were regressively analyzed. Probe into the correlation and the degree of correlation between the calibration sensor and the two standard sensors. Derive regression equation and look forward to regarding as predictor formula, bring about the demarcating of sensor, study its output characteristic. The practice proved the way that using normal linear regression method of Excel in the study of mine dust density sensor output characteristic is easy to realize and has the accurate precision. This method has the good practicability.
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.
By normal linear regression method of Excel, this article1 carries out normal distribution curve fitting with data collection of mine dust density sensor. The experimented data were regressively analyzed. Probe into the correlation and the degree of correlation between the calibration sensor and the two standard sensors. Derive regression equation and look forward to regarding as predictor formula, bring about the demarcating of sensor, study its output characteristic. The practice proved the way that using normal linear regression method of Excel in the study of mine dust density sensor output characteristic is easy to realize and has the accurate precision. This method has the good practicability.
Keywords
calibration; curve fitting; data analysis; mining industry; production engineering computing; regression analysis; sensors; Excel; calibration sensor; data collection; linear regression method; mine dust density sensor output characteristic; normal distribution curve fitting; regression equation; standard sensors; Genetics; Position measurement; Rails; Time measurement; curve fitting; linear regression analysis; normal distribution of Excel; on-line proving;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Application and System Modeling (ICCASM), 2010 International Conference on
Print_ISBN
978-1-4244-7235-2
Type
conf
DOI
10.1109/ICCASM.2010.5619050
Filename
5619050
Link To Document