Website
http://dataportal.arc.gov.au/NCGP/API/grants/DE130100911
Funding Status
Closed
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Funded Activity Summary
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.Funded Activity Details
Start Date: 04-2013
End Date: 12-2019
Funding Scheme: Discovery Early Career Researcher Award
Funding Amount: $339,434.00
Funder: Australian Research Council
Research Topics
ANZSRC Field of Research (FoR)
Pattern Recognition and Data Mining | Database Management | Artificial Intelligence and Image Processing
ANZSRC Socio-Economic Objective (SEO)
Information Processing Services (incl. Data Entry and Capture) |
