A parallel genetic algorithm for seismic velocity optimization
- 出版日期：2000.
- 页数：40 p. :
- 第一责任说明：Gordon Shields.
- 分类号：a631 ; a626
- ISBN：0493022597(ebk.) :
MARC全文
62h0021685 20140523102512.0 cr un||||||||| 101222s2000 xx ||||f|||d||||||||eng | AAI1402333 0493022597(ebk.) : CNY371.35 UnM UnM NGL a631 ; a626 Shields, Gordon. A parallel genetic algorithm for seismic velocity optimization [electronic resource] / Gordon Shields. 2000. 40 p. : digital, PDF file. Source: Masters Abstracts International, Volume: 39-03, page: 0875. ; Adviser: Sushil J. Louis. Thesis (M.S.) -- University of Nevada, Reno, 2000. I investigate a parallel Genetic Algorithm applied to the geophysical inverse problem of seismic travel-time inversion. GAs are search algorithms that mimic the biological processes that control natural selection. The method uses first arrival-times from seismic refraction surveys to invert for the 2-dimensional subsurface velocity field. The parallel implementation follows the “island model,” in which several large subpopulations evolve semi-independently, with periodic migration of individuals between the population “islands.” I design and use modified genetic operators and test our implementation on real data collected from actual field surveys. The parallel GA performs well in terms of both parallel performance and the quality of the optimized velocity models. Comparing with a Simulated Annealing implementation on the same problem, my results qualitatively match the simulated annealing results while taking less time to run. Genetic algorithms. ; Seismic traveltime inversion. University of Nevada, Reno. aCN bNGL http://pqdt.bjzhongke.com.cn/Detail.aspx?pid=UJe07OuSLlY%3d NGL Bs716 rCNY371.35 ; h1 bs1101