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| 吴绍春,吴耿锋,王炜,蔚赵春.寻找地震相关地区的时间序列相似性匹配算法.软件学报,2006,17(2):185-192 |
| 寻找地震相关地区的时间序列相似性匹配算法 |
| A Time-Sequence Similarity Matching Algorithm for Seismological Relevant Zones |
| 投稿时间：2005-03-30 修订日期：2005-07-11 |
| DOI： |
| 中文关键词: 时间序列 相似性匹配 地震预报 算法 粒度 地震相关地区 |
| 英文关键词:time-sequence similarity matching seismological prediction algorithm granularity seismological relevant zones |
| 基金项目:Supported by the National Joint Foundation of Earthquake of China under Grant No. 104090 (国家地震科学联合基金); the Natural Science Foundation of Shanghai Municipality of China under Grant No.03ZR14038 (上海市自然科学基金); the Foundation of Shanghai Municipal Education Commission of China under Grant No.EWL200312(上海高校网格项目) |
| 作者 | 单位 | | 吴绍春 | 上海大学,计算机工程与科学学院,上海,200072 | | 吴耿锋 | 上海大学,计算机工程与科学学院,上海,200072 | | 王炜 | 上海市地震局,上海,200062 | | 蔚赵春 | 上海大学,计算机工程与科学学院,上海,200072 |
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| 摘要点击次数: 3822 |
| 全文下载次数: 3769 |
| 中文摘要: |
| 把时间序列相似性匹配的基本概念和方法引入到地震预报的应用中.在分析现阶段时间序列研究成果的基础上,结合大量地震历史源数据和领域专家经验知识,提出了有关地震地区相关性的地震相似度定义和地震序列相似性匹配模型,并通过大量实验模拟对该模型进行了反复验证,实现了基于地震相似度的时间序列相似性匹配算法.同时,通过分析我国地震活动频繁区域近20年来的地震历史数据,应用地震区域序列相似性匹配算法进行了固定时间差的粗粒度和细粒度纵向序列相似性实验分析,取得了可信度较高的实验结果,为地震学预测的应用研究提供了较好的技术支持. |
| 英文摘要: |
| On the basis of analyzing the newly time sequence research achievement nowadays, several definitions on seismological zone relativity are put forward in this paper for integrating the large amount of history earthquake source data and the experimental expert knowledge in seismological field. At the same time, the time sequence similarity-matching model of the relevant seismological zone is presented, and then it is implemented through several correlative experimental simulations. Based on the sequence similarity-matching model, a sequence-matching algorithm is given with seismological similarity. Furthermore, by discovering the history earthquake database (EQDB) in recent 20 years, some experiments are provided to analyze longitudinal thick-granularity sequential similarity and thin-granularity sequential similarity. Finally, the experimental result has found its satisfactory way out by using the proposed algorithm to support earthquake prediction. |
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