Application of genetic BP network to discriminating earthquakes and explosions

Introduction Artificial Neural Network (ANN) is an important branch of artificial intelligence. It is proposed on the foundation of the study on modern neural science, is a man-made network that can implement some functions based on the mans comprehensive understanding for cerebral neural network (HAN, WANG, 1997). ANN is a mathematical model of simplified human brain neural network and is used to simulate the structures and functions of human brain neural network. ANN is a complex netw…     

Estimation of azimuth and slowness of tele-seismic signals recorded by a local seismic network

Introduction The azimuth and slowness are two major features of seismic signals. The accurate estimation of them is quite important for both phase identification and event location. Generally, there are two types of seismic stations, i.e. 3-component stations (3C) and arrays. To estimate the two direc-tional parameters, the polarization analysis (Jurkevics, 1988) is commonly used for 3C stations and the frequency-wavenumber spectrum analysis ( f-k) (Capon, 1969; Kvaerna, Doornbos, 1986) is …     

Fuzzy neural network models for liquefaction prediction

Integrated fuzzy neural network models are developed for the assessment of liquefaction potential of a site. The models are trained with large databases of liquefaction case histories. A two-stage training algorithm is used to develop a fuzzy neural network model. In the preliminary training stage, the training case histories are used to determine initial network parameters. In the final training stage, the training case histories are processed one by one to develop membership functions for the network parameters. During the testing phase, input variables are described in linguistic terms such as ‘high’ and ‘low’. The prediction is made in terms of a liquefaction index representing the degree of liquefaction described in fuzzy terms such as ‘highly likely’, ‘likely’, or ‘unlikely’. The results from the model are compared with actual field observations and misclassified cases are identified. The models are found to have good predictive ability and are expected to be very useful for a preliminary evaluation of liquefaction potential of a site for which the input parameters are not well defined.     

ARTIFICIAL NEURAL NETWORK CORRECTION OF ROUGH ERRORS OF OBSERVATIONS*

In the context of tower measured radiation datasets.following the correction principle meeting a diagnostic equation in data quality control and in terms of a technique for model construction on data and ANN (artificial neural network) retrieval for BP correction of radiation measurements with rough errors available,a BP model is presented.Evidence suggests that the developed model works well and is superior to a convenient multivariate linear regression model,indicating its wide applications.     

辽宁省地震前兆台网技术改造概述

“九五”期间实施的《辽宁省地震前兆台网技术改造项目》使辽宁省地震前兆观测技术系统由模拟到数字实现了质的飞跃，本文对项目的技术思路，实施情况，取得的成果及建设特色进行了介绍。     

由地方台网记录确定远震信号的方位角和慢度

介绍一种新的适合于地方遥测台网数据处理的方法，估算远震信号到达台站的方位角和慢度．该方法是根据信号在各台站上的到时与台站位置矢量在信号传播方向上的投影之间的相关性的原理．实际分析结果表明，应用该方法对地方台网的记录进行处理时可以准确地计算出信号的方位角和慢度，并能准确快捷地对地方台网记录的远震信号进行解释．      

新疆数字地震前兆台网的数据传输功能分析

为了进一步提高地震前兆数据的传输效率和准确性 ,实现前兆数据采集和管理的自动化 ,对新疆地震局数字化地震前兆台网中心的功能、数据采集原理、数据传输特征进行了分析 ,认为数字化观测技术为地震前兆数据的采集、传输提供了一种高效、可靠的手段     

乌鲁木齐区域数字遥测台网各子台背景噪声分析

选取乌鲁木齐区域数字遥测台网中 1 1个子台的背景噪声数字记录 ,计算并分析其背景噪声地动速度均方根值 RMS、有效测量动态范围以及噪声功率谱 ,最后确定出各台址背景噪声相对集中的频段     

河南豫北地震台网地区波速的探讨

为了解决河南豫北地区地震的定位问题 ,对豫北台网内的 10个典型地震 ,使用了 7个地震台站的资料 ,用波速比求出横波速度 ;用和达定位法 (有的同时使用高桥法 )进行了精确定位 ,求出震源深度 ;测量了震中至各台的震中距 ,以此反算出了纵波速度。通过计算 ,确定出了较为适合河南豫北地震台网地区的波速。     

Establishment of a Non-Permanent GPS Network to Monitor the Recent NE-SW Deformation in the Granada Basin (Betic Cordillera,Southern Spain)

The Granada Basin (Central Betic Cordillera), one of the most seismically active areas of the Iberian Peninsula, is currently subjected to NW-SE compression and NE-SW extension. The present day extension is accommodated by normal faults with various orientations but particularly with a NW-SE strike. At the surface, these active NW-SE normal faults are mainly concentrated on the NE part of the Basin. In this part we have selected a 15-km long segment where several active normal faults crop out. Using the marine Tortonian rocks as a reference, we have calculated a minimum extensional rate of 0.15-0.30 mm/year. The observed block rotation, the listric geometry of faults at depth and the distribution of seismicity over the whole Basin, indicate that this rate is a minimum value. In the framework of an interdisciplinary research project a non-permanent GPS-network has been established in the central sector of Betic Cordillera to monitor the crustal deformations. The first two observation campaigns were done in 1999 and 2000.