A UTEP computational science doctoral student has successfully tied a new mathematical modeling process to the study of earthquakes.
“The model that we applied to the earthquake data was originally applied to financial data,” said Osei Tweneboah, who received his master’s degree from UTEP in 2015. “Financial data is high frequency, which means there are a lot of fluctuations in the data. Earthquake data behaves like the financial data.”
After going through a variety of financial models to find a good fit, Tweneboah zeroed in on one called Ornstein-Uhlenbeck. His modeling will help analyze the effect that earthquakes from long ago have on present and future quakes. The hope is for better understanding of how tectonic stress decays and accumulates during long periods of time — and to potentially estimate when an earthquake could happen.
In May, Tweneboah presented his findings in a paper published in the journal Pure and Applied Geophysics.
Reference:
Maria C. Mariani, Osei K. Tweneboah, Hector Gonzalez-Huizar, Laura Serpa. Stochastic Differential Equation of Earthquakes Series. Pure and Applied Geophysics, 2016; 173 (7): 2357 DOI: 10.1007/s00024-016-1292-1
Note: The above post is reprinted from materials provided by University of Texas at El Paso.
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