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Automated assessment of macroseismic intensity from written sources using the fuzzy sets

机译：使用模糊集自动评估书面来源的宏观地震烈度

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We apply a computer-aided methodology to assess macroseismic intensity from the descriptions reported by documentary material available for eight Italian earthquakes occurred around the beginning of the instrumental era. The procedure consists of three phases: (i) the identification of significant macroseismic effects on the sources and their archiving in a georeferenced database, (ii) the association between the effects and the degrees of the intensity scale by the comparison with traditional estimates made by macroseismic experts, (iii) the assessment of intensities using a multi-attribute decision-making algorithm based on the Fuzzy Sets logic. This work represents a substantial improvement of our previous efforts as we completely redesigned the three phases of the procedure in the light of the experience of the last 10 years and analyzed six further Italian earthquakes so that our database now includes more than 19,000 encoded effects. Our formalized procedure allows to tracing all of the steps of intensity assessment process so that to identify discrepancies with respect to the expert evaluations that might be possibly due to mistakes or to the incomplete account of the available information. Hence, this approach may be useful for providing a systematic and reproducible intensity assessment as well as for supporting standard man-made assessments. The database of effects we have built could also be employed for testing the internal consistency of the macroseismic scale as well as for designing an improved macroseismic scale, based on consistent statistical criteria.
机译：我们采用计算机辅助方法，根据仪器时代初期发生的八次意大利地震的文献资料中的描述，来评估宏观地震烈度。该程序包括三个阶段：（i）识别对震源的重大宏观震害及其在地理参考数据库中的存档，（ii）与传统的估算结果进行比较，将其与强度等级的程度联系起来。宏观地震专家;（iii）使用基于模糊集逻辑的多属性决策算法对强度进行评估。这项工作代表了我们先前工作的实质性改进，因为我们根据过去10年的经验重新设计了程序的三个阶段，并进一步分析了意大利的六次地震，因此我们的数据库现在包含了超过19,000种编码效果。我们的正式程序允许跟踪强度评估过程的所有步骤，以便识别与专家评估有关的差异，这些差异可能是由于错误或对可用信息的不完整描述造成的。因此，这种方法对于提供系统的和可再现的强度评估以及支持标准的人为评估可能是有用的。我们建立的效果数据库也可用于测试宏观地震标度的内部一致性，以及基于一致的统计标准设计改进的宏观地震标度。

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