共查询到18条相似文献,搜索用时 125 毫秒
1.
一种确定大小地震比例的新方法及其在地震预报中的应用 总被引:1,自引:0,他引:1
本利用贝叶斯判别准则,提出了一种确定大小地震比例的新方法,并以1989年山西阳高地震和1983年山东荷泽地震为例,说明了此方法在震预报中应用的可能性,并说明对弱地震活动地区,本方法具有明显的可行性。 相似文献
2.
饱和砂土地震液化判别的分形插值模型 总被引:1,自引:0,他引:1
借鉴分形基本理论,提出了基于分形插值模型的饱和砂土地震液化判别方法.该方法首先选取影响饱和砂土地震液化判别的7个主要因素,根据分类标准,采用在每级标准中随机内插的方法,得到40个标准样本,用于构建饱和砂土地震液化判别的分形插值模型;其次根据最大似然分类原则确定每个饱和砂土地震液化判别指标的评价分维数;然后利用加权求和法计算样本的综合评价值,并根据样本综合评价值与经验等级之间的关系建立分形插值评价模型;最后,进行了实例分析结果表明:该模型的评价结果合理、客观,计算得到的每个样本具体得分值,即使对属于同一级的样本也可以给出其地震液化程度的顺序,为饱和砂土地震液化评价工作提供了一种新的研究方法与思路. 相似文献
3.
采矿、水库蓄水等人类活动可能伴随地震的发生,其突发性和破坏性会对公共安全、社会稳定和经济发展带来威胁。本文围绕国内外矿震、水库地震等非天然地震事件的公共服务需求和相关部门的应急处置措施进行调研分析,发现对于不同类型的地震,公共服务需求存在差异,归纳得到以下针对地震部门和相关单位的应急处置对策建议:震前,完善和落实应急预案,提升建(构)筑物抗震设防等级,规范相关企业行为;震时,判别地震类型并核准地震信息,多部门联动开展应急响应,完善灾情收集渠道;震后,注重科普宣传和舆论疏导。平震结合,多方协调,可有效应对非天然地震事件,维护社会稳定和谐。 相似文献
4.
5.
6.
利用贝叶斯判别准则,提出了一种确定地震活动性参数空间分布函数的方法,并通过计算与比较,说明了该方法的可行性。 相似文献
7.
8.
中国地震局地震应急响应信息服务平台是国家级震后各类应急产品汇聚与共享平台。平台为各级应急指挥人员提供全链条地震应急响应业务信息,为应急指挥决策提供信息支撑。平台具有地震应急服务响应等级信息服务、地震应急产品汇聚、现场灾情汇聚和应急响应工作资料支撑等功能。平台用户涉及中国地震局下属各单位,信息服务内容涉及指挥中心、地震速报、震情研判、灾情快报和现场应急。平台通过用户分组和任务分工实现业务管理和业务工作的无缝衔接,充分发挥整个地震局系统各单位的业务优势,实现各单位应急协同和业务联动,在多次重大破坏性地震应急期间迅速完成了信息的汇聚与共享,为应急处置工作的顺利开展提供了强有力的信息支撑。 相似文献
9.
建筑物倒塌是造成地震人员伤亡的主要原因,对地震应急救援与决策具有重要的指导意义.遥感以其综合、宏观、快速、动态的特点,为地震灾害信息调查和震害快速评估提供了一种可靠的信息源.面向对象的分类方法是针对高分辨率影像的一种新的分类方法.本文在总结遥感影像建筑物震害信息提取方法进展的基础上,将建筑物分为基本完好和毁坏两个等级.选取唐山地震和汶川地震的震后航片,利用面向对象的分类方法来识别影像上基本完好的建筑物,计算评估区内的建筑物倒塌率.实验结果表明,面向对象的分类方法充分利用了图像上的光谱、形状、纹理等特征.在很大程度上克服了基于像元分类方法的局限性,并且基于对象的建筑物倒塌率计算也取得了较好的精度. 相似文献
10.
本文利用GIS技术,将全国地震重点监视防御区(重防区)县级行政单元边界分别与中华人民共和国地震动峰值加速度图和中国及邻区地震区带和潜在震源区划分图叠加,对各县分别计算了如下4个地震危险性指标:(1)县境内最高地震动峰值加速度等级;(2)县境内面积比例最大的地震动峰值加速度等级;(3)县境内最高潜在震源区震级上限等级;(4)县境内面积比例最大的潜在震源区震级上限等级.通过分类统计全国重防区县级行政单元的地震危险性分布,得到的结论是:虽然同为重防区但各地的地震危险性相差巨大.据此,建议根据地震危险性的不同在重防区采取如下措施:第一,不论是何种类型的重防区,均应按中国地震动参数区划图对新建工程做抗震设防,对已有建筑做抗震加固;第二,位于高地震危险性的区域,特别是位于具7级以上潜在地震危险的重防区,要加强与防灾有关的应急准备、城市规划、地震监测预报、地震应急响应等专门措施. 相似文献
11.
地震应急测绘信息对于全面获取震区灾情,针对性援救震灾地区有着重要意义。当前针对震区的测绘信息以独立分类形式存在,缺少数据关联性,在整体信息获取上存在较大缺陷,其地震应急响应能力较差。提出地震应急测绘信息智能综合处理方法,构建地震应急联动信息服务技术平台,设计地震灾情辨识框架;通过判断地震灾情辨识框架,提取地震灾情测绘信息的特征向量,得到地震灾情信息关联规则集,引入测绘数据融合算法,将获取的地震灾情信息进行智能融合,获取地震灾害测绘情况的信息融合结果,实现地震灾情的智能综合性处理。实验结果表明,所提方法在地震应急测绘信息智能综合处理方面具备较强的信息处理与分析能力,具有较强的地震应急响应能力,为我国震后应急指挥工作提供了技术支持。 相似文献
12.
13.
14.
15.
16.
From the events of catastrophic natural disasters that have occurred in recent years, it can be found that social media platforms are increasingly becoming the most important and most convenient way for the general public to timely release and obtain information on disasters. The information obtained from such platforms contains a large amount of information in the form of texts, pictures, etc. that record the current situation of the disaster. And it also has characteristics of high efficiency and high spatial distribution to serve the rapid emergency after the earthquake. In this paper, we firstly make a statistical analysis of 32 689 pieces of historical disaster data acquired from 5 earthquakes with obvious characteristics, such as post-earthquake disaster events, user's expression habits and so on, and adopts cross-validation method. Then information classification system which includes seven first-level categories and more than 50 second-level categories is constructed. The information classification system and evaluation system of crisis degree for post-earthquake emergency response are constructed both using cross-validation method. The former is referred to the thought of existing classification basis and the experience knowledge of several emergency experts. Based on the five indicators of subject word, action word, degree word, time and position measurement, an evaluation system of critically with four levels of severity, moderate intensity, mildness and others was constructed. Considering the sparse features of self-media information and the large difference in the number of training sets, a naive Bayes model for information classification is trained based on the classification system and evaluation system. Its accuracy rate is 73.6%. At the same time, the classification method of feature fusion of machine learning model and semantic calculation model is used to evaluate the criticality of the disaster information. The accuracy rate of the evaluation model is 89.2%, higher than 85.2% of the semantic computing model and 77% of the naive Bayesian model. The evaluation model has combined the advantages of semantic computing method which can evaluate all index features with machine learning method which has high classification efficiency and accuracy. The thresholds for classification between mild and moderate intensity, moderate intensity and severe intensity were 15.2 and 27.39. The model realized in this paper can crawl, classify and evaluate the disaster information in the media in real time after an earthquake, and realizes mining of a small amount of critical and important information from the massive self-media information, thus, to assist in earthquake intensity rapid reporting and accurate rescue. Finally, taking the Jiuzhaigou earthquake on August 8, 2017 as an example, 17 432 pieces of data were crawled in real time within 48 hours after the earthquake. At the same time, based on ArcGIS, the mining information is visualized in time and space, and the availability of the data is evaluated from two perspectives of earthquake intensity quick reporting and accurate rescue after the earthquake. The disaster information of Jiuzhaigou County in the earthquake area is obviously more than that of the non-earthquake area in terms of quantity and emergency degree. The results show that the self-media information with high spatial distribution can effectively find the severer disaster grade area after the earthquake, shorten the time of earthquake intensity prediction, effectively classify and extract information, provide real-time information for precise rescue, and improve the efficiency of emergency response after the earthquake. 相似文献
17.
地震应急灾情信息分类探讨 总被引:5,自引:4,他引:1
收集并整理了多次地震后的灾情信息,结合各类灾情信息的特征和地震应急指挥决策的要求,重点关注地震前灾区的基础信息和震后的地震现场信息,以服务和服从地震应急指挥和抗震救灾为重要目标,将地震应急灾情信息分为震情信息、震区背景信息、灾情信息和应急响应与救援四大类.信息分类结果便于灾情的快速分析与处理,对提高应急决策、救援效率以及应急处置能力具有重要意义. 相似文献