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Special Session on Discovering Seismic Anomalies from Spatial and Temporal Data for Earthquake Study

Strong earthquakes have been the largest menace to human lives since last century, especially being natural disasters to many countries with rapid development and concentrated populations. Considerable efforts from seismological, geological and geophysical areas have been dedicating research on a variety of methods and techniques in order to predict earthquakes and mitigate corresponding risks and damages. Unfortunately the understanding of evolution of earthquakes is very limited, currently there is no widely accepted interpretation for the forming mechanism of earthquakes.

Advances in earth observation technologies driven by the development of satellites provide the ability to capture massive data around earth. Such data contains rich information and a diversity of physical phenomena, some of which might be closely related to earthquakes. A big challenge presented to seismologists is how these data can be effectively processed and wide types of anomalies or precursors can be discovered which are really related to earthquake evolution and preparation.

The main aim of this special session is to establish a communicating platform for researchers and experts in the areas of earthquake science and intelligent data analysis, to foster new collaborations in these two fields and promote the development of data mining technology in discovering seismic anomalies for earthquake study. Therefore we invite contributions on the following topics, but not limited by:

  1. Methods and techniques for detecting concept drifting within sequential data that can be employed in earthquake research
  2. Data fusion technologies for making use of multiple observing data sources for earthquake study
  3. Effective methods for maintaining and accessing large seismic data archives
  4. Intelligent data analysis methods for correlating seismic precursors to earthquakes
  5. Intelligent systems for earthquake prediction
  6. A broad spectrum of probabilistic or soft computing models for risk reduction that can be used to design effective mitigation strategies for communities
  Special Session Organizers:
  • Dr Yaxin Bi, School of Computing and Mathematics, University of Ulster at Jordanstown, UK
  • Prof. Xueming Zhang, Institute of Earthquake Science, China Earthquake Administration, China

  Important Dates:
Paper Submission June 1, 2011
Author Notification August 1, 2011
© 2011 International Conference on Knowledge Science, Engineering and Management (KSEM`2011). All rights reserved.