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Data-Driven Prediction in Complex Systems of Virus Evolution and Global Warming
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作者 LUO Liaofu LÜJun 《内蒙古大学学报(自然科学版)》 2025年第1期1-7,共7页
A complex system is inherently high-dimensional.Recent studies indicate that,even without complete knowledge of its evolutionary dynamics,the future behavior of such a system can be predicted using time-series data(da... A complex system is inherently high-dimensional.Recent studies indicate that,even without complete knowledge of its evolutionary dynamics,the future behavior of such a system can be predicted using time-series data(data-driven prediction).This suggests that the essential dynamics of a complex system can be captured through a low-dimensional representation.Virus evolution and climate change are two examples of complex,time-varying systems.In this article,we show that mutations in the spike protein provide valuable data for predicting SARS-CoV-2 variants,forecasting the possible emergence of the new macro-lineage Q in the near future.Our analysis also demonstrates that carbon dioxide concentration is a reliable indicator for predicting the evolution of the climate system,extending global surface air temperature(GSAT)forecasts through 2500. 展开更多
关键词 data-drivenprediction complex system virus evolution global warming
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