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Pattern recognition applied to earthquake epicenters in California and Nevada

机译:模式识别应用于加利福尼亚和内华达州的地震震中

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摘要

Areas of California and Nevada that are particularly earthquake prone are identified with a computer by applying a pattern-recognition algorithm to standard geological data. The algorithm, which is designed for varied application, defines suites of characteristic traits and successfully discriminates earthquakes characteristic of the San Andreas fault system from those characteristic of the western Basin and Range province. It also pinpoints areas in California and Nevada that are unlikely to be the epicenters of strong earthquakes. Control experiments to test the predictive ability of this technique have shown imperfect but positive results. Predictions of future earthquake epicenters are made. Features characteristic of earthquake-prone areas emerge that appear physically meaningful in terms of large-scale geology. Some of these characteristics were not obvious before.
机译:通过将模式识别算法应用于标准地质数据,可以通过计算机识别加利福尼亚和内华达州特别容易发生地震的地区。该算法 设计用于各种应用,定义了特征 特征的套件,并成功地将圣安德烈亚斯断层系统的地震特征 与这些特征区分开。盆地和山脉省份的 。它还确定了加利福尼亚和内华达州的 地区,这些地区不太可能成为强地震的震中中心。对照实验测试了该技术的预测性,结果并不理想,但结果却是积极的。 容易发生地震的地区的特征表明, 在大范围地质方面具有物理意义。 有些这些特征以前并不明显。

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  • 来源
    《GSA Bulletin》 |1977年第2期|161-173|共13页
  • 作者单位

    Department of Earth and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139;

    Department of Earth and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139;

    Institute of Applied Mathematics, Academy of Sciences of the USSR, Moscow, USSR;

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