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Seismic Signal Discrimination between Earthquakes and Quarry Blasts Using Fuzzy Logic Approach

机译:采用模糊逻辑方法地震和采石场之间的地震信号歧视

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Seismic analysts identify earthquakes signals from those of explosions by visual inspection and calculating some characteristics of seismogram. Such work supposes a great deal of workload for seismic analysts. Therefore, an automatic classification tool reduces dramatically this arduous task, turns classification reliable, removes errors associated to tedious evaluations and changing of personnel. In this present paper we are interested in transforming the analysts' knowledge of classifying seismograms into an automated soft classification system based on fuzzy logic. This is primarily due to its capability of modelling human reasoning and decision-making, managing complexity and controlling computational cost. These capabilities are essential for manipulating high dimensionality and complexity of seismic signal. To conduct effective discrimination, relevant seismogram characteristics are extracted based on human experience. Using these characteristics, a fuzzy classifier is built and tested with real seismic data. The results are found to be encouraging.
机译:地震分析师通过目视检查和计算地震图的一些特征来识别来自爆炸的地震信号。这些工作假设地震分析师的大量工作量。因此,自动分类工具显着降低了这种艰巨的任务,转动分类可靠,从而消除与繁琐的评估和人员更换相关的错误。在本文中,我们有兴趣将分析师对基于模糊逻辑的自动软分类系统转换为分类的分析知识。这主要是由于其建模人工理和决策,管理复杂性和控制计算成本的能力。这些能力对于操纵高维度和地震信号的复杂性至关重要。为了进行有效的歧视,基于人类经验提取相关的地震图特征。使用这些特性,使用真实地震数据构建并测试模糊分类器。发现结果是令人鼓舞的。

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