2 . Artificial intelligence (AI) is showing promise in earthquake prediction, challenging the long-held belief that it is impossible. Researchers at the University of Texas, Austin, have developed an AI algorithm (算法) that correctly predicted 70% of earthquakes a week in advance during a trial in China and provided accurate strength calculations for the predicted earthquakes.
The research team believes their method succeeded because they stuck with a relatively simple machine learning approach. The AI was provided with a set of statistical features based on the team’s knowledge of earthquake physics, and then instructed to train itself using a five-year database of earthquake recordings. Once trained, the AI provided its prediction by listening for signs of incoming earthquakes within the background rumblings (隆隆声) in the Earth.
This work is clearly a milestone in research for AI-driven earthquake prediction. “You don’t see earth-quakes coming,” explains Alexandros Savvaidis, a senior research scientist who leads the Texas Seismological Network Program (TexNet). “It’s a matter of milliseconds, and the only thing you can control is how prepared you are. Even with the 70% accuracy, that’s a huge result and could help minimize economic and human losses and has the potential to remarkably improve earthquake preparation worldwide.”
While it is unknown whether the same approach will work at other locations, the researchers are confident that their AI algorithm could produce more accurate predictions if used in areas with reliable earthquake tracking networks. The next step is to test artificial intelligence in Texas, since UT’s Bureau TexNet has 300 earth-quake stations and over six years worth of continuous records, making it an ideal location for these purposes.
Eventually, the authors hope to combine the system with physics-based models. This strategy could prove especially important where data is poor or lacking. “That may be a long way off, but many advances such as this one, taken together, are what moves science forward,” concludes Scott Tinker, the bureau’s director.
1. How does the AI forecast earthquakes?
| A．By identifying data from the satellites. |
| B．By analyzing background sounds in the Earth. |
| C．By modeling data based on earthquake recordings. |
| D．By monitoring changes in the Earth’s magnetic field. |
2. What does Alexandros Savvaidis intend to show in paragraph 3?
| A．The ways to reduce losses in earthquakes. |
| B．The importance of preparing for earthquakes. |
| C．The significance of developing the AI prediction. |
| D．The limitation of AI algorithms in earthquake prediction. |
3. What will the follow-up research focus on?
| A．Conducting tests in different locations. |
| B．Applying the AI approach to other fields. |
| C．Building more earthquake stations in Texas. |
| D．Enlarging the database to train the calculation accuracy. |
4. Which words can best describe the earthquake-predicting technology?
| A．Stable but outdated. | B．Effective but costly. |
| C．Potential and economical. | D．Pioneering and promising. |
