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Researchers are developing artificial intelligence that can assess the turning points of climate change. Deep learning algorithms can act as an early warning system for runaway climate change.
Chris Bauch, a professor of applied mathematics at the University of Waterloo, is a co-author of a recent research treatise reporting results on new things. Deep learning algorithm.. The study focuses on thresholds that cause rapid or irreversible changes in the system beyond that, Bauf said. “The new algorithm not only predicts, Turning point Not only is it more accurate than existing approaches, but it also provides information about which types of conditions are crossing the turning point, “says Bauf. point It’s not desirable, so I’d like to prevent it if possible. “
Some turning points often associated with runaway Climate change Includes melting of Arctic permafrost. This releases large amounts of methane and can spur even more rapid heating. Collapse of ocean current system. This can lead to near-immediate changes. Weather patternOr the collapse of the ice sheet. This can lead to rapid sea level changes.
According to researchers, this innovative approach to AI is programmed to learn the characteristics of common turning points, not just one type of turning point.
This approach gains its strengths by hybridizing AI and the mathematical theory of turning points, and does more than can be achieved by either method alone. After training AI as a “possible turning point universe” containing about 500,000 models, researchers tested AI at specific real-world turning points in various systems, including historical ones. climate Core sample.
Timothy Renton, director of the Institute for Global Systems at the University of Exeter and one of the co-authors of the study, said: “Providing improved early warnings of climate turning points may help adapt to the coming society and reduce their vulnerability, even if they cannot avoid it. Hmm.”
Deep learning is making great strides Pattern recognition For the first time, researchers have transformed the detection of turning points into a pattern recognition problem. This is done to detect the pattern that occurs before the turning point and to acquire a machine learning algorithm to determine if the turning point is coming.
“People are familiar with the turning points of the climate system, but there are also turning points in ecology and epidemiology, as well as in the stock market,” said McGill University postdoctoral fellow and another co-author of the paper. Thomas Berry said. “What we have learned is that AI is very good at detecting turning point features that are common to a wide variety of complex systems.”
The new deep learning algorithm is “a game changer with the ability to predict major changes, including those related to climate change,” said Madur Anand, another researcher at the project and director of the Guelf Environmental Institute. Says.
Now that the AI has learned the function of the turning point, the team is moving on to the next stage. It is to provide data on modern trends in climate change. But Anand warned about what would happen with such knowledge.
“It definitely goes to us,” she said. “But of course, what we do with this knowledge is up to humanity. We hope that these new discoveries will lead to fair and positive change.”
The paper “Deep Learning of Early Warning Signals at Turning Points” by Bauch, Lenton, Bury, Anand, and co-authors RI Sujith, Induja Pavithran, and Marten Scheffer has been published in the journal. Minutes of the National Academy of Sciences (((PNAS).
For more information:
Thomas M. Bury et al, Deep Learning of Early Warning Signals at Turning Points, Minutes of the National Academy of Sciences (2021). DOI: 10.1073 / pnas.2106140118
Quote: Artificial intelligence is a turning point in climate change acquired on September 23, 2021 from https://phys.org/news/2021-09-artificial-intelligence-reveal-climate-change.html. May be set to reveal)
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