Discovery Projects - Grant ID: DP210100072

复杂动态全局问题的时间序列分类。该项目旨在通过创造新的方法来分析随着时间推移收集的大量数据，从而增加对复杂动态过程的理解。这些新的方法将专门设计，以便以一种适用于许多任务的与应用无关的方式，极大地改善从时间变化数据中获得的对数万亿个全球地球观测数据点的理解。研究成果有望推动时间序列数据分析的理论和实践，实现复杂动力学分析的转型。这将支持工业、商业、政府和研究领域的创新，并扩大许多数据投资的好处，包括澳大利亚政府每年在卫星成像方面的10亿美元投资。

Time Series Classification for Complex Dynamic Global Problems. This project aims to increase understanding of complex dynamic processes by creating new ways of analysing large quantities of data collected over time. These new approaches will be specifically designed to greatly improve the understanding obtained from time varying data for trillions of global earth observation data points in an application-agnostic way that is applicable to many tasks. The outcomes are expected to advance the theory and practice of time-series data analysis and transform the analysis of complex dynamics. This should support innovation in industry, commerce, government and research and magnify benefit from many data investments including the $1 billion Australian governments invest annually in satellite imaging.