用趋势面分析方法提高模拟退火法反演的效率

詹麒; 朱培民

Volume 26 Issue 5

Sep. 2001

Turn off MathJax

Article Contents

Article Navigation > Earth Science > 2001 > 26(5): 538-540

ZHAN Qi, ZHU Pei-min, 2001. AN APPROACH TO IMPROVING EFFICIENCY OF SIMULATED ANNEALING USING TREND SURFACE ANALYSIS. Earth Science, 26(5): 538-540.

Citation:

ZHAN Qi, ZHU Pei-min, 2001. AN APPROACH TO IMPROVING EFFICIENCY OF SIMULATED ANNEALING USING TREND SURFACE ANALYSIS. Earth Science, 26(5): 538-540.

ZHAN Qi, ZHU Pei-min, 2001. AN APPROACH TO IMPROVING EFFICIENCY OF SIMULATED ANNEALING USING TREND SURFACE ANALYSIS. Earth Science, 26(5): 538-540.

Citation:

ZHAN Qi, ZHU Pei-min, 2001. AN APPROACH TO IMPROVING EFFICIENCY OF SIMULATED ANNEALING USING TREND SURFACE ANALYSIS. Earth Science, 26(5): 538-540.

PDF( 358 KB)

AN APPROACH TO IMPROVING EFFICIENCY OF SIMULATED ANNEALING USING TREND SURFACE ANALYSIS

Department of Geophysics, China University of Geosciences, Wuhan 430074, China

Received Date: 2001-03-30
Publish Date: 2001-09-25

Abstract

Abstract

An approach to solving global optimization and inversion problems is developed. It builds 2-order trend surface analysis of abandoned search information in heuristic nonlinear inversion - simulated annealing. The fundamental of this approach is that SA changes process of random search according to prediction of trend surface analysis with some solutions of search in model space so that it ensures inversion to converge to the global optimum fast and exactly. The numerical test of a typical economics inversion problem has proved that this approach can improve the efficiency of simulated annealing remarkably.
- inversion,
- simulated annealing,
- trend surface analysis

FullText(HTML)

References(9)

References

[1]	Kirkpatrick S, Gelatt C D, Vecchi M. Optimization by simulated annealing[J]. Science, 1983, 220: 671-680. doi: 10.1126/science.220.4598.671
[2]	Kaikkonen P, Sharma S P. 2-D nonlinear joint inversion of VLF and VLF-R data using simulated annealing[J]. Journal of Applied Geophysics, 1998, 39(3): 155-176. doi: 10.1016/S0926-9851(98)00025-1
[3]	Sharma S P, Kaikkonen P. Two-dimensional non-linear inversion of VLF-R data using simulated annealing[J]. Geophysical Journal International, 1998, 133(3): 649-668. doi: 10.1046/j.1365-246X.1998.00523.x
[4]	Prasad S N. Simulated annealing 2-D nonlinear inversion of geomagnetic deep sounding data near Ujjain-Guna, India. Pure and Applied Geophysics, 1999, 154(2): 343-363. doi: 10.1007/s000240050233
[5]	姚姚. 地球物理非线性反演模拟退火法的改进[J]. 地球物理学报, 1995, 38(5): 643-650. doi: 10.3321/j.issn:0001-5733.1995.05.011
[6]	Liu P, Hartzell S, Stephenson W. Nonlinear multi-parameter inversion using a hybrid global search algorithm: application in reflection seismology[J]. Geophys J Int, 1995, 122: 991-1000. doi: 10.1111/j.1365-246X.1995.tb06851.x
[7]	Chunduru R K, Sen M K, Stoffa P L. Hybrid optimization methods for geophysical inversion[J]. Geophysics, 1997, 62: 1196-1207. doi: 10.1190/1.1444220
[8]	Judge G G. The theory and practice of econometrics. 2nd ed. New York: John Wiley and Sons, 1985. 956-957.
[9]	Goffe B, Ferrier G, Rogers J. Global optimization of statistical functions with simulated annealing[J]. Journal of Econometrics, 1994, 60(1/2): 65-100.