Efficient and effective methods for classifying massive time series data

该项目旨在改变时间序列分类的理论和实践。目前的技术水平无法处理描述人类面临的许多关键问题（如疾病传播和气候变化）的大量时间序列。该项目旨在开发能够在全球范围内分析动态过程的方法，在给定的计算预算内提供最准确的分类器。该项目的预期成果包括高效、有效和广泛适用的时间序列分类技术。这将为众多部门带来巨大的好处，改变时间序列问题的数据科学，并支持工业，商业和政府的创新。

This project aims to transform the theory and practice of time series classification. The current state of the art cannot handle the massive numbers of time series that describe many critical problems facing humanity, such as disease transmission and climate change. This project seeks to develop methods that can analyse dynamic processes at global scale, delivering the most accurate classifiers feasible within a given computational budget. Expected outcomes of this project include efficient, effective and broadly applicable time series classification technologies. This should provide significant benefits to myriad sectors, transforming data science for time series problems and supporting innovation in industry, commerce and government.