Layered neural networks based analysis of radon concentration and environmental parameters in earthquake prediction

被引:45
作者
Negarestani, A
Setayeshi, S
Ghannadi-Maragheh, M
Akashe, B
机构
[1] Amir Kabir Univ Technol, Fac Phys & Nucl Sci, Tehran, Iran
[2] Atom Energy Org Iran, Tehran, Iran
[3] Univ Tehran, Iran Geophys Ctr, Tehran, Iran
关键词
radon; neural networks; environmental parameters; earthquake prediction;
D O I
10.1016/S0265-931X(01)00165-5
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
A layered neural network (LNN) has been employed to estimate the radon concentration in soil related to the environmental parameters. This technique can find any functional relationship between the radon concentration and the environmental parameters. Analysis of the data obtained from a site in Thailand indicates that this approach is able to differentiate time variation of radon concentration caused by environmental parameters from those arising by anomaly phenomena in the earth (e.g. earthquake). This method is compared with a linear computational technique based on impulse responses from multivariable time series. It is indicated that the proposed method can give a better estimation of radon variations related to environmental parameters that may have a non-linear effect on the radon concentration in soil, such as rainfall. (C) 2002 Elsevier Science Ltd. All rights reserved.
引用
收藏
页码:225 / 233
页数:9
相关论文
共 16 条
[1]   DISLOCATION MODEL FOR RADON RESPONSE TO DISTANT EARTHQUAKES [J].
FLEISCHER, RL .
GEOPHYSICAL RESEARCH LETTERS, 1981, 8 (05) :477-480
[2]   ARTIFICIAL NEURAL NETWORKS IN MANUFACTURING - CONCEPTS, APPLICATIONS, AND PERSPECTIVES [J].
HUANG, SH ;
ZHANG, HC .
IEEE TRANSACTIONS ON COMPONENTS PACKAGING AND MANUFACTURING TECHNOLOGY PART A, 1994, 17 (02) :212-228
[3]   Progress in supervised neural networks [J].
Hush, Don R. ;
Horne, Bill G. .
IEEE SIGNAL PROCESSING MAGAZINE, 1993, 10 (01) :8-39
[4]   GROUNDWATER RADON ANOMALIES ASSOCIATED WITH EARTHQUAKES [J].
IGARASHI, G ;
WAKITA, H .
TECTONOPHYSICS, 1990, 180 (2-4) :237-254
[5]   EPISODIC RADON CHANGES IN SUBSURFACE SOIL GAS ALONG ACTIVE FAULTS AND POSSIBLE RELATION TO EARTHQUAKES [J].
KING, CY .
JOURNAL OF GEOPHYSICAL RESEARCH, 1980, 85 (NB6) :3065-3078
[6]   A STATISTICAL APPROACH TO LEARNING AND GENERALIZATION IN LAYERED NEURAL NETWORKS [J].
LEVIN, E ;
TISHBY, N ;
SOLLA, SA .
PROCEEDINGS OF THE IEEE, 1990, 78 (10) :1568-1574
[7]  
Lippmann R. P., 1987, IEEE ASSP Magazine, V4, P4, DOI 10.1145/44571.44572
[8]   METHOD FOR CONTINUOUS MEASUREMENT OF RADON IN GROUNDWATER FOR EARTHQUAKE PREDICTION [J].
NOGUCHI, M ;
WAKITA, H .
JOURNAL OF GEOPHYSICAL RESEARCH, 1977, 82 (08) :1353-1357
[9]   Signal processing of soil gas radon, atmospheric pressure, moisture, and soil temperature data: A new approach for radon concentration modeling [J].
Pinault, JL ;
Baubron, JC .
JOURNAL OF GEOPHYSICAL RESEARCH-SOLID EARTH, 1996, 101 (B2) :3157-3171
[10]   Temporal variations of radon in soil related to earthquakes [J].
Planinic, J ;
Radolic, V ;
Lazanin, Z .
APPLIED RADIATION AND ISOTOPES, 2001, 55 (02) :267-272