[Cite as http://purl.org/au-research/grants/arc/DE130100911]
Dr Jing He
(Discovery Early Career Researcher Award)
Brief description Accurate and online abnormality detection in multiple correlated time series. This study will develop a new kernel-based and online support vector regression method for real-time and correlated multiple time series and promote their use in critical applications, which will save money and lives. Examples include the detection of stock market crisis events and detection of patients' condition deterioration in the operating theatre.
Funding Amount $339,434
Funding Scheme Discovery Early Career Researcher Award
View this grant in the ARC Data Portal