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基于人工神经网络的珠江三角洲地壳稳定性研究
引用本文:詹美珍,詹文欢,姚衍桃. 基于人工神经网络的珠江三角洲地壳稳定性研究[J]. 华南地震, 2010, 30(3): 11-20
作者姓名:詹美珍  詹文欢  姚衍桃
作者单位:1. 中国科学院边缘海地质重点实验室,中国科学院南海海洋研究所,广东,广州,510301;中国科学院研究生院,北京,100039
2. 中国科学院边缘海地质重点实验室,中国科学院南海海洋研究所,广东,广州,510301
基金项目:国家自然基金委与广东省联合基金项目 
摘    要:
应用BP神经网络方法建立了珠江三角洲地壳稳定性的评价模型。首先在前人研究基础上,分析了珠江三角洲的地震活动、断层发育程度、地壳垂直形变、第四系厚度及地热分布等特征,然后收集相应的数据,建立这些影响因子与地壳稳定性之间相关性的转化原则,对这些数据进行标准化转化,建立并训练BP人工神经网络模型,由模型的实际输出插值得出珠江三角洲地壳稳定性的等值线图。与前人对该区地壳稳定性的定性及定量分析对比表明,该模型的评价结果与前人研究结果基本一致,因此基于神经网络的珠江三角洲地壳稳定性评价模型是比较可靠的。

关 键 词:地震活动  珠江三角洲  地壳稳定性  BP人工神经网络

Evaluation of Regional Crust of the Pearl River Delta Based on BP Artificial Neural Network
ZHAN Meizhen,ZHAN Wenhuan,YAO Yantao. Evaluation of Regional Crust of the Pearl River Delta Based on BP Artificial Neural Network[J]. South China Journal of Seismology, 2010, 30(3): 11-20
Authors:ZHAN Meizhen  ZHAN Wenhuan  YAO Yantao
Affiliation:1.CAS Key Laboratory of Margirual Sea Geology, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou 510301, China; 2. Gradnate University of Chinese Academy of Sciences, Beijing 100039, China)
Abstract:
BP artificial netural network is introduced to study the crustal stability of the Pearl River Delta. Based on previous studies, this paper analyzes the characteristics of seismic activity, the development of faults, the crustal deformation rate, Quaternary sediments and distribution of geothermal features and collects relevant data, and then builds the transformation relationship between these impact factors and the crustal stability. Based on this, these data are transformed into a number between 0 and 1, and the BP ANN model is developed and trained. The result of the method of BP ANN relatively conforms to reality and is much more accurate than other models.
Keywords:Seismic activity  The Pearl River Delta  The crustal stability  BPR Artificial Neural Network
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