Artificial Intelligence Revolutionizes Earthquake Prediction Months in Advance
Scientists have now found out how to use artificial intelligence to predict major earthquakes even months before they happen and this discovery resulted from research conducted at the University of Alaska Fairbanks (UAF). Artificial intelligence methods are now taught to distinguish such precursors in enormous datasets of seismic data to predict the occurrence of seismic events. It can be said that this discovery can prove to be the end of many lives and also reduce the loss caused by the earthquake to the population globally.
The paper conducted by Társilo Girona of the University of Alaska Fairbanks Geophysical Institute aims at long wavelength magnetotelluric low-frequency tectonic activity at large scales with the help of deep learning systems. For preparing the algorithm, the research team fed data for the past 30 years of earthquake data collected from Alaska and California to the artificial intelligence model.
Successful Predictions: Anchorage and Ridgecrest Earthquakes
To test the effectiveness of their artificial intelligence approach, Girona and his team applied the model to two significant earthquakes: for example, the November 2018 magnitude 7. 1 Anchorage, Alaska earthquake as well as the 2019 Ridgecrest, California, earthquake sequence. Notably, the AI algorithm identified low-magnitude seismic activity over about 15 to 25% of these areas about three months prior to the each event.
A case in point is the Anchorage earthquake that happened in Alaska and destroyed so much infrastructure; the network used artificial intelligence to alert people of the signs of the large-scale event. The model predicted a probability of 80 per cent that a major earthquake would occur in the next 30 days, about three months before the actual event of the major earthquake. This probability was 60% before the occurrence of earthquakes, whereas in the days preceding the quake, this probability reached 85%, thus proving that the created artificial intelligence model really works.
The Science Behind AI Earthquake Prediction
Scientists suggest that elevated fluid pressure within the fault reduces friction along the fault and generates activity at low magnitudes with the largest earthquakes in the sequence. This shift in responsibility results in stress being distributed in an inconsistent manner across the region, resulting in lesser quakes that act as precursors.
Machine learning does a great job in detecting such fine details within massive sets of seismic data, allowing experts to see possible threats months beforehand. Girona further focused on the future of application of artificial intelligence in earthquake prediction, saying that, ‘It is here that the improvement in machine learning and high performance computing becomes crucial to helping the researchers sift through meaningful patterns that may be indicative of an impending earthquake.
Challenges and Future Developments
Despite these possibilities, an objective number of aspects has been cited as follows and researchers know there are a lot of difficulties in the future. It should be tested nearly in real-time in order to solve the problems in a forecasting and trained using local historical seismic data before deploying the algorithm in new locations. It also important to note that false alarms, and failed predictions are in some way unethical and practically costly to communities they are made on.
Nevertheless, the application of artificial intelligence in prediction of the earthquake has shown considerable advancement in the study of earthquakes. Of course, we hope that as we progress in research we will be receiving even more accurate and timely forecasts that will minimize the number of lives and infrastructures being lost.
It is now becoming apparent that earthquake prediction will be revolutionized with the help of artificial intelligence. Only by means of big data and machine learning approaches researchers can look at the possibility opening in the area of seismic forecasting. With the advancement in artificial intelligence models coupled with the increased utilization of the same, the world is steadily getting closer to the day when devastating earthquakes can be predicted with more precision than ever before and therefore the needed time to prepare and respond is available.
