DocumentCode
533040
Title
Notice of Retraction
Model study on the principal dimensions of the revolving floating crane based on SVM
Author
Chaoguang Jin ; Yanyun Yu ; Yunlong Wang ; Yan Lin
Author_Institution
State Key Lab. of Struct. Anal. for Ind. Equip., Dalian Univ. of Technol., Dalian, China
Volume
13
fYear
2010
fDate
22-24 Oct. 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.
During the design of the revolving floating crane, mathematical model for the principal dimensions is not available at present. In the paper, on the basis of collecting and classifying the crane´s principal dimensions, the mathematical model for the principal dimensions of the revolving floating crane is developed using the SVM,in which the relationship between the lifting capacity and main dimensions has been established respectively. The model is helpful for mastering the essential variation rules on the crane´s principal dimensions and can be used for technical and economic demonstration during its design. Practical result shows that the method of SVM possesses better regression ability than BP neural network´s, which provides a new method to forecast the crane´s principal dimensions.
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.
During the design of the revolving floating crane, mathematical model for the principal dimensions is not available at present. In the paper, on the basis of collecting and classifying the crane´s principal dimensions, the mathematical model for the principal dimensions of the revolving floating crane is developed using the SVM,in which the relationship between the lifting capacity and main dimensions has been established respectively. The model is helpful for mastering the essential variation rules on the crane´s principal dimensions and can be used for technical and economic demonstration during its design. Practical result shows that the method of SVM possesses better regression ability than BP neural network´s, which provides a new method to forecast the crane´s principal dimensions.
Keywords
backpropagation; civil engineering computing; cranes; lifting; neural nets; support vector machines; BP neural network; SVM; crane principal dimensions; economic demonstration; lifting capacity; mathematical model; model study; revolving floating crane; technical demonstration; Artificial neural networks; Biological system modeling; Cranes; Kernel; Marine vehicles; Mathematical model; Support vector machines; BP neural network; Support Vector Machine (SVM); principal dimensions; revolving floating crane;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Application and System Modeling (ICCASM), 2010 International Conference on
Conference_Location
Taiyuan
Print_ISBN
978-1-4244-7235-2
Type
conf
DOI
10.1109/ICCASM.2010.5622723
Filename
5622723
Link To Document