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Artificial Neural Network Model for Discrimination of Stability of Ancient Landslide in Impounding Area of three gorges.Project, China

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Journal of China University of Geosciences 2003年第2期14卷 161-165页

作者： Zhou Pinggen China Institute of Geo environment Monitoring, Beijing 100081 China Institute of Geo-environment Monitoring Beijing 100081

The factors of geomorphology, geological setting, effect of ground water and environment dynamic factors (e.g. rainfall and artificial water recharge) should be integrated in the discrimination of the stability of the ancient landslide. As the criterion of landslide stability has been studied, the artificial neural network model was then applied to discriminate the stability of the ancient landslide in the impounding area of the three gorges.project on the Yangtze River, China. The model has the property of self adaptive identifying and integrating complex qualitative factors and quantitative factors. The results of the artificial neural network model are coincided well with what were gained by classical limit equilibrium analysis (the Bishop method and Janbu method) and by other comprehensive discrimination methods.

关键词： ancient landslide stability artificial neural network model the three gorges.

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An Evaluation of Reverse-Time Imaging of Clustering Earthquakes

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Journal of Earth Science 2015年第4期26卷 548-555页

作者： Zhihui Zou Hua-Wei Zhou Aifei Bian Jianzhong Zhang Lei Xing College of Marine Geosciences Ocean University of China Department of Earth & Atmospheric Sciences University of Houston Institute of Geophysics and Geomatics China University of Geosciences

Clustering earthquakes refer to the seismic events that occur closely with each other in time and space. Because their overlapping waveform records make it difficult to pick the first arrivals, the hypocenters of clustering earthquakes cannot be determined accurately by traveltime location methods. Here we apply a reverse-time imaging （RTI） method to map clustering earthquakes. Taking the advantage of directly using waveforms, the RTI method is capable to map either a single small earthquake or some densely distributed clustering earthquakes beneath a 2-D seismic array. In 3-D case the RTI method is successfully applied to locate the long-offset doublet earthquakes using the data from a set of sparsely distributed surface stations. However, for the same acquisition geometry, the RTI encounters challenges in mapping densely distributed clustering earthquakes. While it is obvious that improving the mapping of clustering earthquakes requires a denser receiver network with wider range of illumination angles, it is necessary to verify the actual resolution of the RTI method with synthetic data. In our study area in the three gorges.region, our tests in 3-D case suggest that some events beneath the linear aligned sub-arrays have reasonable resolution.

关键词： clustering earthquakes reverse-time imaging hypocentral location microseismie the three gorges.

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