TY - GEN
T1 - Inversion on S-wave velocity structure of shallow soil layer site using parallel genetic algorithm
AU - Dong, Liancheng
AU - Li, Guangying
AU - Tao, Xiaxin
AU - Lu, Dagang
AU - Liu, Juan
AU - Hu, Xinfu
PY - 2011
Y1 - 2011
N2 - Microtremors was developed to inverse S-wave velocity structure of sites because it costs little and easy to monitor, can be performed at any place even in a densely populated city with non-destructive measurements, the genetic algorithm is widely used in inversion and there are many disadvantages in using genetic algorithms to solve practical problems, so the authors did a lot of efforts to overcome these disadvantages. In order to solve these disadvantages, a coarse-grained parallel genetic algorithm(PGA) based on personal computer cluster was proposed to inverse S-wave velocity structure of shallow soil layer of actual engineering sites, the simulated annealing algorithm and parallel technique message passing interface(MPI) were adopted to implement the coarse-grained parallel compute. The subpopulations were collaboratively optimized through individual migration strategy and the dynamic populations were adopted to balance the computing load. The shallow S-wave velocity structures of two examples and the actual engineering sites were inversed through a 4-node PC cluster test system, the results showed that the algorithm has a good parallel efficiency and can be used in engineering site.
AB - Microtremors was developed to inverse S-wave velocity structure of sites because it costs little and easy to monitor, can be performed at any place even in a densely populated city with non-destructive measurements, the genetic algorithm is widely used in inversion and there are many disadvantages in using genetic algorithms to solve practical problems, so the authors did a lot of efforts to overcome these disadvantages. In order to solve these disadvantages, a coarse-grained parallel genetic algorithm(PGA) based on personal computer cluster was proposed to inverse S-wave velocity structure of shallow soil layer of actual engineering sites, the simulated annealing algorithm and parallel technique message passing interface(MPI) were adopted to implement the coarse-grained parallel compute. The subpopulations were collaboratively optimized through individual migration strategy and the dynamic populations were adopted to balance the computing load. The shallow S-wave velocity structures of two examples and the actual engineering sites were inversed through a 4-node PC cluster test system, the results showed that the algorithm has a good parallel efficiency and can be used in engineering site.
KW - Inversion
KW - Load balance
KW - Parallel genetic algorithm
KW - S-wave velocity structure
UR - https://www.scopus.com/pages/publications/79958044370
U2 - 10.4028/www.scientific.net/AMR.243-249.319
DO - 10.4028/www.scientific.net/AMR.243-249.319
M3 - 会议稿件
AN - SCOPUS:79958044370
SN - 9783037851258
T3 - Advanced Materials Research
SP - 319
EP - 322
BT - Advances in Civil Engineering and Architecture
T2 - 1st International Conference on Civil Engineering, Architecture and Building Materials, CEABM 2011
Y2 - 18 June 2011 through 20 June 2011
ER -