-
- Sriram Aditya
- University of Ontario Institute of Technology (UOIT)
-
- Rahanamayan Shahryar
- University of Ontario Institute of Technology (UOIT)
-
- Bourennani Farid
- University of Ontario Institute of Technology (UOIT)
この論文をさがす
抄録
<p>Earthquakes are natural disasters caused by an unexpected release of seismic energy from extreme levels of stress within the earth’s crust. Over the years, earthquake prediction has been a controversial research subject that has challenged even the smartest of minds. Because numerous seismic precursors and other factors exist that may indicate the potential of an earthquake occurring, it is extremely difficult to predict the exact time, location, and magnitude of an impending quake. Nevertheless, evaluating a combination of these precursors through advances in Artificial Intelligence (AI) can certainly increase the possibility of predicting an earthquake. The sole purpose for predicting a seismic event at a pre-determined locality is to provide substantial time for the citizens to take precautionary measures. With this in mind, Artificial Neural Networks (ANNs) have been promising techniques for the detection and prediction of locally impending earthquakes based on valid seismic information. To highlight the recent trends in earthquake abnormality detection, including various ideas and applications, in the field of Neural Networks, valid papers related to ANNs are reviewed and presented herein.</p>
収録刊行物
-
- Journal of Advanced Computational Intelligence and Intelligent Informatics
-
Journal of Advanced Computational Intelligence and Intelligent Informatics 18 (5), 701-713, 2014-09-20
富士技術出版株式会社
- Tweet
詳細情報 詳細情報について
-
- CRID
- 1390001288151325952
-
- NII論文ID
- 130007673228
-
- NII書誌ID
- AA12042502
-
- ISSN
- 18838014
- 13430130
-
- NDL書誌ID
- 025788149
-
- 本文言語コード
- en
-
- データソース種別
-
- JaLC
- NDL
- Crossref
- CiNii Articles
-
- 抄録ライセンスフラグ
- 使用不可