کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4692321 1636792 2013 14 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Earthquake prediction in seismogenic areas of the Iberian Peninsula based on computational intelligence
ترجمه فارسی عنوان
پیش بینی زلزله در مناطق زلزله زده شبه جزیره ایبرین بر اساس هوش محاسباتی
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه علوم زمین و سیارات فرآیندهای سطح زمین
چکیده انگلیسی


• Development of a system capable of predicting earthquakes for the next seven days
• Application of ANN is particularly reliable to earthquake prediction.
• Use of geophysical information modeling the soil behavior as ANN's input data
• Successful analysis of one region with large seismic activity

A method to predict earthquakes in two of the seismogenic areas of the Iberian Peninsula, based on Artificial Neural Networks (ANNs), is presented in this paper. ANNs have been widely used in many fields but only very few and very recent studies have been conducted on earthquake prediction. Two kinds of predictions are provided in this study: a) the probability of an earthquake, of magnitude equal or larger than a preset threshold magnitude, within the next 7 days, to happen; b) the probability of an earthquake of a limited magnitude interval to happen, during the next 7 days. First, the physical fundamentals related to earthquake occurrence are explained. Second, the mathematical model underlying ANNs is explained and the configuration chosen is justified. Then, the ANNs have been trained in both areas: The Alborán Sea and the Western Azores–Gibraltar fault. Later, the ANNs have been tested in both areas for a period of time immediately subsequent to the training period. Statistical tests are provided showing meaningful results. Finally, ANNs were compared to other well known classifiers showing quantitatively and qualitatively better results. The authors expect that the results obtained will encourage researchers to conduct further research on this topic.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Tectonophysics - Volume 593, 8 May 2013, Pages 121–134
نویسندگان
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