DocumentCode :
2462056
Title :
Calculation of angle parameters of non-principle section observation station under thick loose bed
Author :
Wang, Lieping ; Hu, Kui ; Cheng, Yuping ; Chen, Yincui
Author_Institution :
Sch. of Earth & Environ. Eng., Anhui Univ. of Sci. & Technol., Huainan, China
fYear :
2011
fDate :
24-26 June 2011
Firstpage :
4853
Lastpage :
4856
Abstract :
In this paper, with the low precision of angle parameters of non-principle section observation station which was calculated under thick loose bed, from the perspective of amending stochastic model, the conception of fitting weight was concluded based on analyzing the residual sequence of subsidence. The sequence of subsidence was used to construct fitting weight model of probability integral method based on least squares estimation. The author designs 3 computing solutions, and analyses various solution´s fitting result from the perspective of residual sequence of subsidence, critical deformation value, mean square error of residual and so on. At last, The main conclusions is that, in the condition of thick loose bed,the whole fitting result of equal weighted estimate is better than unequal weighted estimate,and the fitting weight 1/|Wi| could effectively improve the calculation precision of boundary angle and movement angle.
Keywords :
least mean squares methods; mining; probability; stochastic processes; angle parameters; boundary angle; critical deformation value; fitting weight; least squares estimation; mean square error; movement angle; nonprinciple section observation station; probability integral method; residual sequence; stochastic model; thick loose bed; Analytical models; Coal; Coal industry; Educational institutions; Fitting; Presses; Publishing; angle parameters; fitting weight; probability integral method; residual sequence; stochastic model; subsidence;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Remote Sensing, Environment and Transportation Engineering (RSETE), 2011 International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4244-9172-8
Type :
conf
DOI :
10.1109/RSETE.2011.5965399
Filename :
5965399
Link To Document :
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