Abstract
Discussions were given on a genetic algorithm as a means to solve simultaneously the problems related to stability of solution and dependence on an initial model in estimating subsurface structures using the microtremor exploration method. In the study, a forking genetic algorithm (fGA) to explore solid substance groups was applied to the optimizing simulations for a velocity structure model to discuss whether the algorithm can be used practically. The simulation No. 1 was performed by making the number of layers four for both of the given velocity structure and the optimizing model. On the other hand, the simulation No. 2 was executed by making the number of layers for the given velocity structure greater than that for the optimizing model. As a result, it was verified that wide range exploration may be possible for the velocity structure model, and that a large number of candidates for the velocity structure model may be proposed. In either case, the exploration capability of the fGA exceeded that of the standard simple genetic algorithm. 8 refs., 4 figs., 2 tabs.
Cho, I;
Nakanishi, I;
[1]
Ling, S;
[2]
Okada, H
[3]
- Kyoto University, Kyoto (Japan)
- Nihon Nessui Corp., Tokyo (Japan)
- Hokkaido University, Sapporo (Japan)
Citation Formats
Cho, I, Nakanishi, I, Ling, S, and Okada, H.
Application of forking genetic algorithm to the estimation of an S-wave-velocity structure from Rayleigh-wave dispersion data. With special reference to an exploration method using microtremors; Rayleigh ha no bunsan data kara S ha sokudo kozo wo suiteisuru inversion mondai eno kotaigun tansaku bunkigata identeki algorithm no tekiyo. Bido tansaho ni kanrenshite.
Japan: N. p.,
1997.
Web.
Cho, I, Nakanishi, I, Ling, S, & Okada, H.
Application of forking genetic algorithm to the estimation of an S-wave-velocity structure from Rayleigh-wave dispersion data. With special reference to an exploration method using microtremors; Rayleigh ha no bunsan data kara S ha sokudo kozo wo suiteisuru inversion mondai eno kotaigun tansaku bunkigata identeki algorithm no tekiyo. Bido tansaho ni kanrenshite.
Japan.
Cho, I, Nakanishi, I, Ling, S, and Okada, H.
1997.
"Application of forking genetic algorithm to the estimation of an S-wave-velocity structure from Rayleigh-wave dispersion data. With special reference to an exploration method using microtremors; Rayleigh ha no bunsan data kara S ha sokudo kozo wo suiteisuru inversion mondai eno kotaigun tansaku bunkigata identeki algorithm no tekiyo. Bido tansaho ni kanrenshite."
Japan.
@misc{etde_622642,
title = {Application of forking genetic algorithm to the estimation of an S-wave-velocity structure from Rayleigh-wave dispersion data. With special reference to an exploration method using microtremors; Rayleigh ha no bunsan data kara S ha sokudo kozo wo suiteisuru inversion mondai eno kotaigun tansaku bunkigata identeki algorithm no tekiyo. Bido tansaho ni kanrenshite}
author = {Cho, I, Nakanishi, I, Ling, S, and Okada, H}
abstractNote = {Discussions were given on a genetic algorithm as a means to solve simultaneously the problems related to stability of solution and dependence on an initial model in estimating subsurface structures using the microtremor exploration method. In the study, a forking genetic algorithm (fGA) to explore solid substance groups was applied to the optimizing simulations for a velocity structure model to discuss whether the algorithm can be used practically. The simulation No. 1 was performed by making the number of layers four for both of the given velocity structure and the optimizing model. On the other hand, the simulation No. 2 was executed by making the number of layers for the given velocity structure greater than that for the optimizing model. As a result, it was verified that wide range exploration may be possible for the velocity structure model, and that a large number of candidates for the velocity structure model may be proposed. In either case, the exploration capability of the fGA exceeded that of the standard simple genetic algorithm. 8 refs., 4 figs., 2 tabs.}
place = {Japan}
year = {1997}
month = {Oct}
}
title = {Application of forking genetic algorithm to the estimation of an S-wave-velocity structure from Rayleigh-wave dispersion data. With special reference to an exploration method using microtremors; Rayleigh ha no bunsan data kara S ha sokudo kozo wo suiteisuru inversion mondai eno kotaigun tansaku bunkigata identeki algorithm no tekiyo. Bido tansaho ni kanrenshite}
author = {Cho, I, Nakanishi, I, Ling, S, and Okada, H}
abstractNote = {Discussions were given on a genetic algorithm as a means to solve simultaneously the problems related to stability of solution and dependence on an initial model in estimating subsurface structures using the microtremor exploration method. In the study, a forking genetic algorithm (fGA) to explore solid substance groups was applied to the optimizing simulations for a velocity structure model to discuss whether the algorithm can be used practically. The simulation No. 1 was performed by making the number of layers four for both of the given velocity structure and the optimizing model. On the other hand, the simulation No. 2 was executed by making the number of layers for the given velocity structure greater than that for the optimizing model. As a result, it was verified that wide range exploration may be possible for the velocity structure model, and that a large number of candidates for the velocity structure model may be proposed. In either case, the exploration capability of the fGA exceeded that of the standard simple genetic algorithm. 8 refs., 4 figs., 2 tabs.}
place = {Japan}
year = {1997}
month = {Oct}
}