We are happy to introduce a new Special Focus Issue titled:
Data Mining for Earthquake Prediction and Analysis
Earthquakes and related geohazards continue to pose serious risks to human life, infrastructure, and ecosystems. Anticipating these events is a scientific priority that involves a combination of environmental observations, historical data, and advanced analytical techniques. As the volume of seismic and geological data grows, data mining has become an essential tool in uncovering hidden patterns and correlations that can inform predictive models and risk assessments.
This special issue seeks to highlight recent advancements and innovative approaches in using data-driven techniques for earthquake analysis. Researchers are encouraged to submit original research and review articles focusing on applications of artificial intelligence, machine learning, big data processing, and computational models in seismic hazard prediction and interpretation.
Topics relevant to this issue may include:
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Predictive modeling of seismic events using historical data
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Clustering algorithms for seismic pattern recognition
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Early warning systems based on intelligent data analytics
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AI-driven tools for post-event impact evaluation
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Application of regression, neural networks, and deep learning in seismic forecasting
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Big data frameworks for earthquake resilience in urban settings
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Feature extraction from P and S waves for magnitude estimation
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Comparative performance of data mining methods in disaster analysis
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Smart infrastructure and data-driven emergency planning
Submission Details
đź“Ś Now Open for Submissions
đź“Ś Submission Deadline: January 30, 2026
📌 Submission Instructions: Authors should select the section titled “SFI: Earthquake Data Mining” when uploading their manuscript through the journal’s submission system.
Please note: The schedule for this issue may be updated based on the volume of submissions and editorial planning.
Guest Editorial Team
Dr. Rahmat Widia Sembiring
Department of Computer and Informatics, Politeknik Negeri Medan, Indonesia
Dr. Jasni Mohammad Zain
Institute for Big Data Analytics and Artificial Intelligence (IBDAAI), Universiti Teknologi MARA, Malaysia
Dr. Tao Hai
School of Computer and Information, Qiannan Normal University for Nationalities, China
We invite contributions from across disciplines including seismology, computer and data science, civil engineering, and disaster management. This issue will serve as a platform for advancing the integration of data science in addressing earthquake-related challenges and fostering future-ready urban resilience.
