A network communication and recording system for digital seismic observation

Introduction Digital seismic observation systems originated from 1970′s. It has developed greatly in the past 30 years up to now. Its performances were improved, dynamic range and resolution increased a lot, the power consumption decreased a lot, and so on (YOU et al, 2003a, b). In a word, the dream of broad frequency-band, big dynamic range, digitalization of seismic observation has come true already. But, the previous digital seismic observation systems only support communica-tion based o…     

防震减灾技术系统网络应用中的网络安全

扼要介绍计算机网络安全结构及Internet网络应用中的数据服务。国家防震减灾技术系统网络中心计算机网络的组成及安全。介绍了Internet提供的服务；网络中心与Internet的2个出口以及它提供的DNS、FTP、E－MAIL、WWW等服务。重点介绍网络中心的防火墙安全及防火墙的过滤作用。     

建立地震信息服务系统的网络安全管理体系的探索

以国际信息安全标准BS7799/ISO17799为信息安全管理体系的准则,根据《中国地震局信息安全等级保护建设方案》的相关要求和规定,通过分析信息网络的层次关系,在科学的安全框架之上,探讨建立以防火墙系统、VPN应用系统、网络反病毒软件,以及入侵检测系统(IDS)安全策略为核心的地震信息服务系统网络安全管理体系构。     

A hybrid machine learning ensemble approach based on a Radial Basis Function neural network and Rotation Forest for landslide susceptibility modeling: A case study in the Himalayan area,India

In this paper, a hybrid machine learning ensemble approach namely the Rotation Forest based Radial Basis Function (RFRBF) neural network is proposed for spatial prediction of landslides in part of the Himalayan area (India). The proposed approach is an integration of the Radial Basis Function (RBF) neural network classifier and Rotation Forest ensemble, which are state-of-the art machine learning algorithms for classification problems. For this purpose, a spatial database of the study area was established that consists of 930 landslide locations and fifteen influencing parameters (slope angle, road density, curvature, land use, distance to road, plan curvature, lineament density, distance to lineaments, rainfall, distance to river, profile curvature, elevation, slope aspect, river density, and soil type). Using the database, training and validation datasets were generated for constructing and validating the model. Performance of the model was assessed using the Receiver Operating Characteristic (ROC) curve, area under the ROC curve (AUC), statistical analysis methods, and the Chi square test. In addition, Logistic Regression (LR), Multi-layer Perceptron Neural Networks (MLP Neural Nets), Naïve Bayes (NB), and the hybrid model of Rotation Forest and Decision Trees (RFDT) were selected for comparison. The results show that the proposed RFRBF model has the highest prediction capability in comparison to the other models (LR, MLP Neural Nets, NB, and RFDT); therefore, the proposed RFRBF model is promising and should be used as an alternative technique for landslide susceptibility modeling.     

海底地震监测网络发展现状

近年来随着地面与空间的遥测遥感通信技术,特别是随之衍生而来的海底光纤电缆技术的发展,海洋学者可以从海底回头向上观测整个海洋世界,对深入海底做近距离和全天候监测海洋信息变为可能。近年来许多国家正在逐步策划和建设以海啸减灾为目的,以海底电缆为主轴、海底地震监测为核心内容的海底观测网络。本文分别针对美国、加拿大、欧洲、日本以及中国多种典型海底观测网的主要观测技术进行分析,提出发展中国海底地震监测网络的建议。     

安徽省地震信息网络数据动态备份措施的研究

信息技术的广泛应用在给人们带来极大便利的同时,也带来了某些隐患,一旦数据丢失或损坏将造成巨大损失。本文介绍了目录复制、数据库复制和Arc SDE数据库引擎3种数据动态备份技术的具体实现方法。实际应用表明,采用这些方法,可在多台服务器之间动态备份地震信息网络数据。     

内蒙古区域地震台网监测能力研究

国际上新近发展的“基于概率的完整性震级”(PMC)方法,具有可考察地震定位中由于台站人为选择等造成的台网监测能力下降,以及避免传统基于G-R关系的统计算法因地震数目过少而无法评估等优点.本研究利用PMC方法,计算得到内蒙古区域地震台网39个台站对周边地震事件的检测概率及台网检测概率.单台检测概率结果显示:PMC方法能够客观地反映39个台站对地震事件的检测能力;因台网布局等影响,内蒙古区域地震台网中西部和中东部地区的台站检测能力较强,而靠近蒙古、俄罗斯边境的台站, 阿拉善右旗附近地区的台站,以及邻近吉林、黑龙江等地区的台站检测能力较低.合成检测概率结果显示,由于邻省台站的引入,全区80%的地区基于概率的最小完整性震级M_P达到2.2左右,其余地区M_P达到3.3左右.为提高地震台网监测能力,建议在监测能力较弱的中蒙交界地区、东北部地区,以及阿拉善左旗以西地区适度加密台站,进一步优化台网布局.     

基于强震台网的我国沿海海啸走时预警

经济快速发展的中国沿海地区,面临着潜在海啸袭击危险。海啸传播走时分析是海啸预警系统的重要组成部分。本文基于强震台网提供的地震要素,从理论上讨论海啸预警时间计算方法。在球坐标系下,建立了远洋海啸传播模型,采用差分技术,实现远洋海啸传播数值模拟,首次针对我国主要城市进行了海啸走时计算,分析了我国沿海走时特点,指出了未来发生在太平洋的远洋海啸对我国的长江三角洲会有较大影响。本文计算海啸走时方法可以为我国建设的新一代基于数值海啸预警系统提供技术支持。     

A GIS-based comparative study of hybrid fuzzy-gene expression programming and hybrid fuzzy-artificial neural network for land subsidence susceptibility modeling

Stochastic Environmental Research and Risk Assessment - Land subsidence is a complicated hazard that artificial intelligence models can model it without approximation and simplification. In this...