Time Series Classification for Complex Dynamic Global Problems

该项目旨在通过创建分析长期收集的大量数据的新方法来增加对复杂动态过程的理解。这些新方法将被专门设计，以一种适用于许多任务的与应用无关的方式，极大地提高对数万亿全球地球观测数据点时变数据的理解。研究结果有望推动时间序列数据分析的理论和实践，并改变复杂动力学的分析。这将支持工业、商业、政府和研究的创新，并扩大许多数据投资的收益，包括澳大利亚政府每年投资10亿美元用于卫星成像。

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.