Journal papers

2020

  • Hussam Abdelkarim, Matthew Durie, Rinaldo Bellomo, Christoph Bergmeir, Omar Badawi, Khaled El-Khawas, David Pilcher (2020) A comparison of characteristics and outcomes of patients admitted to the ICU with asthma in Australia and New Zealand and United States. In: Journal of Asthma, 57, (4), pp. 398-404 (IF 2.081, Q3 in ``Respiratory System'', JCR 2018). Abstract DOI bib
  • H. Bandara, C. Bergmeir, S. Smyl (2020) Forecasting Across Time Series Databases using Recurrent Neural Networks on Groups of Similar Series: A Clustering Approach. In: Expert Systems with Applications, 140, pp. 112896 (IF 4.292, Q1 in ``Computer Science, Artificial Intelligence'', JCR 2018). Abstract  pdf bib
  • D Rajapaksha, C Bergmeir, W Buntine (2020) LoRMIkA: Local Rule-based Model Interpretability with k-optimal Associations. In: Information Sciences, (forthcoming). Abstract DOI  pdf bib
  • Kasun Bandara, Christoph Bergmeir, Hansika Hewamalage (2020) LSTM-MSNet: Leveraging Forecasts on Sets of Related Time Series with Multiple Seasonal Patterns. In: IEEE Transactions on Neural Networks and Learning Systems, (forthcoming). Abstract  pdf bib
  • Hansika Hewamalage, Christoph Bergmeir, Kasun Bandara (2020) Recurrent Neural Networks for Time Series Forecasting: Current Status and Future Directions. In: International Journal of Forecasting, (forthcoming). Abstract  pdf bib

2019

  • Diva Baggio, Trisha Peel, Anton Peleg, Sharon Avery, Madhurima Prayaga, Michelle Foo, Gholamreza Haffari, Ming Liu, Christoph Bergmeir, Michelle Ananda-Rajah (2019) Closing the gap in surveillance and audit of invasive mold diseases for antifungal stewardship using machine learning. In: Journal of Clinical Medicine, 8, (9), pp. 1390 (IF 5.688, Q1 in ``Medicine, General & Internal'', JCR 2018). Abstract bib

2018

  • F.J. Baldan, S. Ramirez-Gallego, C. Bergmeir, F. Herrera, J. M. Benitez (2018) A Forecasting Methodology for Workload Forecasting in Cloud Systems. In: IEEE Transactions on Cloud Computing, 6, (4), pp. 929-941 (IF 5.967, top 4% (Q1) in ``Computer Science, Information Systems'', and top 7% (Q1) in ``Computer Science, Theory & Methods'', JCR 2018). Abstract DOI bib
  • C. Bergmeir, R. J. Hyndman, B. Koo (2018) A Note on the Validity of Cross-Validation for Evaluating Autoregressive Time Series Prediction. In: Computational Statistics and Data Analysis, 120, pp. 70-83 (IF 1.323, Q2 ranking in ``Statistics & Probability'', JCR 2018). Abstract DOI bib
  • Shane Nanayakkara, Sam Fogarty, Michael Tremeer, Kelvin Ross, Brent Richards, Christoph Bergmeir, Sheng Xu, Dion Stub, Karen Smith, Mark Tacey, Danny Liew, David Pilcher, David M Kaye (2018) Characterising risk of in-hospital mortality following cardiac arrest using machine learning: A retrospective international registry study. In: PLoS Medicine, 15 (11): e1002709, pp. 1-16 (IF 11.048, top 5% (Q1) in ``Medicine, General & Internal'', JCR 2018). Abstract DOI bib
  • Fotios Petropoulos, Rob J Hyndman, Christoph Bergmeir (2018) Exploring the sources of uncertainty: why does bagging for time series forecasting work?. In: European Journal of Operational Research, 268, pp. 545-554 (IF 3.806, Q1 in ``Operations Research & Management Sciences'', JCR 2018). Abstract bib
  • Daniel Peralta, Christoph Bergmeir, Martin Krone, Marta Galende, Manuel Menendez, Gregorio I Sainz-Palmero, Carlos Martinez Beltrand, Frank Klawonn, Jose M Benitez (2018) Multiobjective Optimization for Railway Maintenance Plans. In: Journal of Computing in Civil Engineering, 32, (3), pp. 04018014, 1-11 (IF 2.554, Q2 in ``Engineering, Civil'' and Q2 in ``Computer Science, Interdisciplinary Applications'', JCR 2018). Abstract bib
  • M. Gonzalez, C. Bergmeir, I. Triguero, Y. Rodriguez, J. M. Benitez (2018) Self-labeling techniques for semi-supervised time series classification: an empirical study. In: Knowledge and Information Systems, 55, (2), pp. 493-528 (IF 2.397, Q2 in ``Computer Science, Information Systems'' and Q2 in ``Computer Science, Artificial Intelligence'', JCR 2018). Abstract DOI bib

2017

  • Christoph Bergmeir, Irma Bilgrami, Christopher Bain, Geoffrey I. Webb, Judit Orosz, David Pilcher (2017) Designing a more efficient, effective and safe Medical Emergency Team (MET) service using data analysis. In: PLoS ONE, 12 (12): e0188688, (12), pp. 1-13 (IF 2.766, Q1 in ``Multidisciplinary Sciences'', JCR 2017). Abstract DOI bib
  • Lahn David Straney, Andrew A Udy, Aidan Burrell, Christoph Bergmeir, Sue Huckson, D James Cooper, David V Pilcher (2017) Modelling risk-adjusted variation in length of stay among Australian and New Zealand ICUs. In: PLoS ONE, 12 (5): e0176570, pp. 1-12 (IF 2.766, Q1 in ``Multidisciplinary Sciences'', JCR 2017). Abstract DOI bib
  • Michelle R. Ananda-Rajah, Christoph Bergmeir, Francois Petitjean, Monica A. Slavin, Karin A. Thursky, Geoffrey I. Webb (2017) Toward Electronic Surveillance of Invasive Mold Diseases in Hematology-Oncology Patients: An Expert System Combining Natural Language Processing of Chest Computed Tomography Reports, Microbiology, and Antifungal Drug Data. In: JCO Clinical Cancer Informatics, (1), pp. 1-10. Abstract DOI bib

2016

  • C. Bergmeir, R. J. Hyndman, J. M. Benitez (2016) Bagging Exponential Smoothing Methods using STL Decomposition and Box-Cox Transformation. In: International Journal of Forecasting, 32, pp. 303-312 (IF 2.642, Q1 in ``Economics'', JCR 2016). Abstract bib
  • C. Bergmeir, D. Molina, J. M. Benitez (2016) Memetic Algorithms with Local Search Chains in R: The Rmalschains Package. In: Journal of Statistical Software, 75, (4), pp. 1-33 (IF 9.436, Q1 in ``Computer Science, Interdisciplinary Research'', and ``Statistics & Probability'', JCR 2016). Abstract DOI  pdf bib
  • M. Gonzalez, C. Bergmeir, I. Triguero, Y. Rodriguez, J. M. Benitez (2016) On the Stopping Criteria for k-Nearest Neighbor in Positive Unlabeled Time Series Classification Problems. In: Information Sciences, 328, pp. 42-59 (IF 4.832, Q1 in ``Computer Science, Information Systems'', JCR 2016). Abstract bib

2015

  • L. S. Riza, C. Bergmeir, F. Herrera, J. M. Benitez (2015) frbs: Fuzzy Rule-Based Systems for Classification and Regression in R. In: Journal of Statistical Software, 65, (6), pp. 1-30 (IF 2.379, Q1 in ``Computer Science, Interdisciplinary Research'', and Q1 in ``Statistics & Probability'', JCR 2015). Abstract DOI  pdf bib

2014

  • L. S. Riza, A. Janusz, C. Bergmeir, C. Cornelis, F. Herrera, D. Slezak, J. M. Benitez (2014) Implementing algorithms of rough set theory and fuzzy rough set theory in the R package ``RoughSets''. In: Information Sciences, 287, (10), pp. 68-89 (IF 4.038, Q1 in ``Computer Science, Information Systems'', JCR 2014). Abstract bib
  • C. Bergmeir, M. Costantini, J. M. Benitez (2014) On the usefulness of cross-validation for directional forecast evaluation. In: Computational Statistics and Data Analysis, 76, pp. 132-143 (IF 1.400, Q2 in ``Statistics & Probability'' and Q3 in ``Computer Science, Interdisciplinary Applications'', JCR 2014). Abstract bib

2013

  • A. Santos-Lozano, F. Santin-Medeiros, G. Cardon, G. Torres-Luque, R. Bailon, C. Bergmeir, J.R. Ruiz, A. Lucia, N. Garatachea (2013) The Actigraph GT3X Accelerometer: validation and determination of physical intensity cut points across age-groups. In: Int J Sports Med., 34, pp. 975-982 (IF 2.374, Q1 in ``Sports Sciences'', JCR 2013). Abstract bib

2012

  • C. Bergmeir, J. M. Benitez (2012) Neural Networks in R Using the Stuttgart Neural Network Simulator: RSNNS. In: Journal of Statistical Software, 46, (7), pp. 1-26 (IF 4.910, Q1 in ``Computer Science, Interdisciplinary Research'', and Q1 in ``Statistics & Probability'', JCR 2012). Abstract DOI  pdf bib
  • C. Bergmeir, J. M. Benitez (2012) On the use of cross-validation for time series predictor evaluation. In: Information Sciences, 191, pp. 192-213 (IF 3.643, Q1 in ``Computer Science, Information Systems'', JCR 2012). Abstract bib
  • C. Bergmeir, M. Garcia Silvente, J. M. Benitez (2012) Segmentation of Cervical Cell Nuclei in High-resolution Microscopic Images: A new Algorithm and a Web-based Software Framework. In: Computer Methods and Programs in Biomedicine, 107, (3), pp. 497-512 (IF 1.555, Q1 in the category ``Computer Science, Theory & Methods'' and Q2 in ``Computer Science, Interdisciplinary Applications'', JCR 2012). Abstract DOI bib
  • C. Bergmeir, I. Triguero, D. Molina, J. L. Aznarte, J. M. Benitez (2012) Time Series Modeling and Forecasting Using Memetic Algorithms for Regime-switching Models. In: IEEE Transactions on Neural Networks and Learning Systems, 23, (11), pp. 1841-1847 (IF 3.766, Q1 ranking in the categories ``Computer Science, Artificial Intelligence'', ``Computer Science, Hardware & Architecture'', and ``Computer Science, Theory & Methods'', JCR 2012). Abstract DOI bib

2009

  • C. Bergmeir, M. Seitel, C. Frank, R. de Simone, H.-P. Meinzer, I. Wolf (2009) Comparing calibration approaches for 3D ultrasound probes. In: International Journal of Computer Assisted Radiology and Surgery, 4, (2), pp. 203-213. Abstract DOI bib

Working papers

2020

  • Mahdi Abolghasemi, Rob J Hyndman, Garth Tarr, Christoph Bergmeir (2020) Machine learning applications in time series hierarchical forecasting. In: Working Paper. Abstract  pdf bib
  • Rakshitha Godahewa, Chang Deng, Arnaud Prouzeau, Christoph Bergmeir (2020) Simulation and Optimisation of Air Conditioning Systems using Machine Learning. In: Working Paper. Abstract  pdf bib
  • Chang Wei Tan, Christoph Bergmeir, Francois Petitjean, Geoffrey I. Webb (2020) Time Series Regression. In: Working Paper. Abstract  pdf bib

2019

  • D Rajapaksha, C Tantithamthavorn, C Bergmeir, W Buntine (2019) Generating Rule-based Explanations for the Predictions of Defect Models. In: Working Paper. Abstract bib

2016

  • L. S. Riza, C. Bergmeir, F. Herrera, J. M. Benitez (2016) A Universal Representation Framework for Fuzzy Rule-Based Systems Based on PMML. In: Working Paper. Abstract  pdf bib
  • M. Gonzalez, R. Osmani, J.D. Rodriguez, C. Bergmeir, I. Triguero, J. M. Benitez (2016) ssc: An R Package for Semi-Supervised Classification. In: Working Paper. Abstract  pdf bib

Papers in refereed conference proceedings

2020

  • Rakshitha Godahewa, Trevor Yann, Christoph Bergmeir, Francois Petitjean (2020) Seasonal Averaged One-Dependence Estimators: A Novel Algorithm to Address Seasonal Concept Drift in High-Dimensional Stream Classification. In: International Joint Conference on Neural Networks (IJCNN), 19 - 24 July, 2020, Glasgow (UK) (forthcoming). Abstract  pdf bib
  • Kasun Bandara, Christoph Bergmeir, Sam Campbell, Debbie Scott, Dan Lubman (2020) Towards Accurate Predictions and Causal `What-if' Analyses for Planning and Policy-making: A Case Study in Emergency Medical Services Demand. In: International Joint Conference on Neural Networks (IJCNN), 19 - 24 July, 2020, Glasgow (UK) (forthcoming). Abstract  pdf bib

2019

  • H. Bandara, P. Shi, C. Bergmeir, H. Hewamalage, Q. Tran, B. Seaman (2019) Sales Demand Forecast in E-commerce using a Long Short-Term Memory Neural Network Methodology. In: 26th International Conference on Neural Information Processing (ICONIP) 2019, December 12 - 15, Sydney (Australia). Abstract  pdf bib

2014

  • S. Maslyuk, C. Bergmeir, K. Rotaru (2014) Identifying Jumps and Cojumps for Assets of Different Asset Classes. In: Australasian Conference of Economists (ESAM/ACE) 2014, July 1-4, Hobart (Tasmania). Abstract bib
  • L. S. Riza, C. Bergmeir, F. Herrera, J. M. Benitez (2014) Learning from Data Using the R Package ``frbs''. In: Fuzzy Systems (FUZZ-IEEE), 2014 IEEE World Congress on Computational Intelligence (WCCI), July 6-11, Beijing (China). Abstract bib

2013

  • C. Bergmeir, G. Sainz, C. Martinez-Bertrand, J. M. Benitez (2013) A Study on the Use of Machine Learning Methods for Incidence Prediction in High-Speed Train Tracks. In: Proceedings IEA/AIE 2013, June 17-21, Amsterdam (The Netherlands). Abstract bib

2012

  • C. Bergmeir, I. Triguero, F. Velasco, J. M. Benitez (2012) Optimización de Modelos Estadísticos y Difusos para el Análisis de Series Temporales Mediante Evolución Diferencial. In: Actas del XVI Congreso Español sobre Tecnologías y Lógica Fuzzy (ESTYLF2012), Valladolid (Spain), February 2012.. Abstract bib
  • C. Bergmeir, I. Triguero, F. Velasco, J. M. Benitez (2012) Optimization of neuro-coefficient smooth transition autoregressive models using differential evolution. In: Proceedings of the Seventh International Conference on Hybrid Artificial Intelligence Systems (HAIS 2012), Salamanca (Spain). Lecture Notes in Computer Science 7208, pp. 464-473. Abstract bib

2011

  • C. Bergmeir, J. M. Benitez (2011) Forecaster performance evaluation with cross-validation and variants. In: International Conference on Intelligent Systems Design and Applications, ISDA, pp. 849-854. Abstract bib
  • J. M. Benitez, J. L. Aznarte, C. Bergmeir (2011) Research on Time Series at the DiCITS Lab. In: Actas de la XIV Conferencia de la Asociación Española para la Inteligencia Artificial (CAEPIA11), Tenerife (Spain), November 2011.. Abstract bib

2010

  • C. Bergmeir, M. Garcia Silvente, J. Esquivias Lopez-Cuervo, J. M. Benitez (2010) Segmentation of Cervical Cell Images using Mean-shift Filtering and Morphological Operators. In: Proc. SPIE, Vol. 7623, 76234C. Abstract DOI bib

2009

  • C. Bergmeir, N. Subramanian (2009) Klassifikation von Standardebenen in der 2D-Echokardiographie mittels 2D-3D-Bildregistrierung. In: Bildverarbeitung für die Medizin, Heidelberg: Springer, pp. 222-226. Abstract bib
  • C. Bergmeir, N. Subramanian (2009) Operator Guidance in 2D Echocardiography via 3D Model to Image Registration. In: Proc. SPIE, Vol. 7265, 726518. Abstract DOI bib

2008

  • C. Bergmeir, M. Seitel, C. Frank, R. de Simone, H.-P. Meinzer, I. Wolf (2008) 3D Ultrasound: A Comparison of Calibration Methods. In: International Journal of Computer Assisted Radiology and Surgery. Abstract bib
  • C. Bergmeir, M. Seitel, C. Frank, R. de Simone, H.-P. Meinzer, I. Wolf (2008) Entwicklung und Evaluation einer Kalibrierungsmethode für 3D-Ultraschall. In: Bildverarbeitung für die Medizin, Heidelberg: Springer, pp. 237-241. Abstract bib

Other Conference Publications (Reviewed By Program Committee Alone)

2019

  • H. Bandara, C. Bergmeir, H. Hewamalage (2019) Forecasting Time Series with Multiple Seasonal Patterns using a Long Short-Term Memory Neural Network Methodology. In: 39th International Symposium on Forecasting (ISF) 2019, June 16 - 19, Thessaloniki (Greece). Abstract bib
  • S. Smyl, C. Bergmeir (2019) R Rlgt package - Bayesian Extensions of Exponential Smoothing models. In: 39th International Symposium on Forecasting (ISF) 2019, June 16 - 19, Thessaloniki (Greece). Abstract bib
  • H. Hewamalage, C. Bergmeir, H. Bandara (2019) Recurrent Neural Networks for Time Series Forecasting: An Overview and Empirical Evaluations. In: 39th International Symposium on Forecasting (ISF) 2019, June 16 - 19, Thessaloniki (Greece). Abstract bib

2018

  • H. Abdelkarim, M. Durie, K. El-Khawas, R. Bellomo, C. Bergmeir, O. Badawi (2018) Comparison of characteristics and outcomes of patients admitted to the ICU with asthma in Australia, New Zealand and United States. In: Australian Critical Care, Elsevier, pp. 114. Abstract DOI bib
  • M. Gonzalez, R. Osmani, J. Rodriguez, C. Bergmeir, I. Triguero, J. M. Benitez (2018) ssc: An R Package for Semi-Supervised Classification. In: Proceedings useR! 2018, July 10-13, Brisbane (Australia). Abstract bib

2017

  • H. Bandara, C. Bergmeir, S. Smyl (2017) Forecasting Sets of Similar Time Series with Recurrent Neural Networks. In: 37th International Symposium on Forecasting (ISF) 2017, June 26 - 28, Cairns (Australia). Abstract bib

2016

  • C. Bergmeir, R. J. Hyndman, B. Koo (2016) A Note on the Validity of Cross-Validation for Evaluating Time Series Prediction. In: 36th International Symposium on Forecasting (ISF) 2016, June 19 - 22, Santander (Spain). Abstract bib
  • F. Petropoulos, R. J. Hyndman, C. Bergmeir (2016) Exploring the Sources of Uncertainty: Why does Bagging Work?. In: 36th International Symposium on Forecasting (ISF) 2016, June 19 - 22, Santander (Spain). Abstract bib

2015

  • C. Bergmeir, I. Bilgrami, C. Bain, G. Webb, D. Pilcher (2015) Using data mining techniques to build a more efficient medical emergency team service. In: ANZICS, Safety and Quality Conference: The Deteriorating Patient, July 6-7, Gold Coast, Australia. Abstract bib

2014

  • C. Bergmeir, R. J. Hyndman, J. M. Benitez (2014) Bagging Exponential Smoothing Methods using STL Decomposition and Box-Cox Transformation. In: 34th International Symposium on Forecasting (ISF) 2014, June 29 - July 2, Rotterdam (The Netherlands). Abstract bib
  • J. M. Benitez, L. S. Riza, C. Bergmeir, D. Peralta, F. Herrera (2014) R as a PaaS cloud computing service for Computational Intelligence tasks. In: Proceedings useR! 2014, June 30 - July 3, Los Angeles (California). Abstract bib

2013

  • L. S. Riza, C. Bergmeir, F. Herrera, J. M. Benitez (2013) Constructing fuzzy rule-based systems with the R package frbs. In: Proceedings useR! 2013, July 10-12, Albacete (Spain). Abstract bib
  • C. Bergmeir, M. Costantini, J. M. Benitez (2013) On the usefulness of the cross-validation for directional forecast evaluation. In: 7th International Conference on Computational and Financial Econometrics 2013, December 2013, London. Abstract bib
  • C. Bergmeir, J. M. Benitez, J. Bermudez, J.V. Segura, E. Vercher (2013) Rsiopred: An R package for forecasting by exponential smoothing with model selection by a fuzzy multicriteria approach. In: Proceedings useR! 2013, July 10-12, Albacete (Spain). Abstract bib