EVALUATING ROBUSTNESS OF A HMM-BASED CLASSIFICATION SYSTEM OF VOLCANO-SEISMIC EVENTS AT COLIMA AND POPOCATEPETL VOLCANOES

机译：评估科里马和Popocateppetl火山的火山地震事件的基于HMM的分类系统的鲁棒性

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This work presents a continuous volcano-seismic classification system based in the Hidden Markov Models as solution to recently strong needs for automatic event detection and recognition methods in early warning and monitoring scenarios. Furthermore, our system includes a reliable method to assign confidence measures to the recognized signals in order to evaluate the robustness of the results. Data from the two most active volcanoes have been used to probe the system reliability on a complex joint corpus achieving a recognition accuracy higher than 78% in blind recognition tests.

机译：这项工作介绍了基于隐马尔可夫模型的连续火山地震分类系统，作为最近在预警和监测方案中的自动事件检测和识别方法的最近需要的解决方案。此外，我们的系统包括可靠的方法，以为识别的信号分配置信度措施，以便评估结果的稳健性。来自两个最活跃的火山的数据已被用于探测在盲识别测试中实现高于78％的复杂联合语料库上的系统可靠性。

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《International Geoscience and Remote Sensing Symposium》|2009年||共4页
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作者
Guillermo Cortes; Raul Arambula; Ligdamis A. Gutierrez; Carmen Benitez; Jesus Ibanez; Philippe Lesage; Isaac Alvarez; Luz Garcia;
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中图分类 P3-53;
关键词
Volcano monitoring; Classification; Hidden Markov Models; Volcano-seismic events; Reliability;

机译：火山监测;分类;隐藏马尔可夫模型;火山地震事件;可靠性;

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4. EVALUATING ROBUSTNESS OF A HMM-BASED CLASSIFICATION SYSTEM OF VOLCANO-SEISMIC EVENTS AT COLIMA AND POPOCATEPETL VOLCANOES [C] . Guillermo Cortes, Raul Arambula, Ligdamis A. Gutierrez, International Geoscience and Remote Sensing Symposium . 2009

机译：评估科里马和Popocateppetl火山的火山地震事件的基于HMM的分类系统的鲁棒性
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EVALUATING ROBUSTNESS OF A HMM-BASED CLASSIFICATION SYSTEM OF VOLCANO-SEISMIC EVENTS AT COLIMA AND POPOCATEPETL VOLCANOES

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