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Projects 2016 2017

FFT2: New mathematical models for data handling phase 2

Smith-Miles, K., Munoz Acosta, A., Kandanaarachchi, S. & Katsifolis, J.

1/11/1630/06/17

Project: Research

Research Output 2012 2019

  • 5 Article
  • 1 Conference Paper

A framework for automated anomaly detection in high frequency water-quality data from in situ sensors

Leigh, C., Alsibai, O., Hyndman, R. J., Kandanaarachchi, S., King, O. C., McGree, J. M., Neelamraju, C., Strauss, J., Talagala, P. D., Turner, R. D. R., Mengersen, K. & Peterson, E. E., 10 May 2019, In : Science of the Total Environment. 664, p. 885-898 14 p.

Research output: Contribution to journalArticleResearchpeer-review

Anomaly detection in streaming nonstationary temporal data

Talagala, P. D., Hyndman, R. J., Smith-Miles, K., Kandanaarachchi, S. & Muñoz, M. A., 2019, (Accepted/In press) In : Journal of Computational and Graphical Statistics. 15 p.

Research output: Contribution to journalArticleResearchpeer-review

Predicting sediment and nutrient concentrations from high-frequency water-quality data

Leigh, C., Kandanaarachchi, S., McGree, J. M., Hyndman, R. J., Alsibai, O., Mengersen, K. & Peterson, E. E., Aug 2019, In : PLoS ONE. 14, 8, 22 p., e0215503.

Research output: Contribution to journalArticleResearchpeer-review

Open Access
File

Machine learning methods for predicting the outcome of hypervelocity impact events

Ryan, S., Thaler, S. & Kandanaarachchi, S., 1 Mar 2016, In : Expert Systems with Applications. 45, p. 23-39 17 p.

Research output: Contribution to journalArticleResearchpeer-review

Support Vector Machines for characterising Whipple shield performance

Ryan, S., Kandanaarachchi, S. & Smith-Miles, K., 2015, Proceedings of the 2015 Hypervelocity Impact Symposium (HVIS 2015). Schonberg, W. P. (ed.). Elsevier, p. 522-529 8 p. (Procedia Engineering; vol. 103).

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review