DocumentCode
3347981
Title
Notice of Retraction
Back analysis of thermal parameters of roller compacted concrete dam based on parallel particle swarm optimization
Author
Xiaofei Zhang ; Xianfeng Huai ; Shouyi Li ; Bo Yang
Author_Institution
Inst. of Water Resources & Hydroelectric Eng., Xi´an Univ. of Technol., Xi´an, China
Volume
4
fYear
2011
fDate
26-28 July 2011
Firstpage
2011
Lastpage
2014
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.
According to the randomness of thermal parameters of laboratory test and the defects of traditional back analysis method which is easy to fall into premature and has low efficiency and great computational complexity, the back analysis method based on parallel particle swarm optimization is developed. The back analysis steps of thermal parameters of mass concrete structure is demonstrated detailedly. When three-dimensional finite element relocating mesh method and improved BP neural network method are used to inverse thermal parameters based on the measured temperature, the parameters which reflect the true performance can be obtained. The results show that this method has a better stability and convergency and is feasible to inverse thermal parameters.
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.
According to the randomness of thermal parameters of laboratory test and the defects of traditional back analysis method which is easy to fall into premature and has low efficiency and great computational complexity, the back analysis method based on parallel particle swarm optimization is developed. The back analysis steps of thermal parameters of mass concrete structure is demonstrated detailedly. When three-dimensional finite element relocating mesh method and improved BP neural network method are used to inverse thermal parameters based on the measured temperature, the parameters which reflect the true performance can be obtained. The results show that this method has a better stability and convergency and is feasible to inverse thermal parameters.
Keywords
backpropagation; computational complexity; concrete; dams; mesh generation; neural nets; particle swarm optimisation; random processes; structural engineering computing; BP neural network method; back analysis method; computational complexity; convergency; inverse thermal parameters; mass concrete structure; measured temperature; parallel particle swarm optimization; randomness; roller compacted concrete dam; stability; three-dimensional finite element relocating mesh method; Atmospheric measurements; Concrete; Particle measurements; Particle swarm optimization; Temperature; Temperature measurement; Thermal analysis; back analysis; measured temperature; parallel particle swarm optimization; thermal parameter; three-dimensional finite element relocating mesh method;
fLanguage
English
Publisher
ieee
Conference_Titel
Natural Computation (ICNC), 2011 Seventh International Conference on
Conference_Location
Shanghai
ISSN
2157-9555
Print_ISBN
978-1-4244-9950-2
Type
conf
DOI
10.1109/ICNC.2011.6022398
Filename
6022398
Link To Document