Efficient and effective analytics for real-world time series forecasting

Research output

Research output per year 2020 2020 2021 2022 2022

• 12 Article
• 1 Conference Paper

Research output per year

Research output per year

Search results

• 2022

  An accurate and fully-automated ensemble model for weekly time series forecasting

  Godahewa, R., Bergmeir, C., Webb, G. I. & Montero-Manso, P., 19 Mar 2022, (Accepted/In press) In: International Journal of Forecasting. 18 p.

  Research output: Contribution to journal › Article › Research › peer-review

• Forecast evaluation for data scientists: common pitfalls and best practices

  Hewamalage, H., Ackermann, K. & Bergmeir, C., 2022, (Accepted/In press) In: Data Mining and Knowledge Discovery. 45 p.

  Research output: Contribution to journal › Article › Research › peer-review

  Open Access
  1 Citation (Scopus)

• Global models for time series forecasting: a simulation study

  Hewamalage, H., Bergmeir, C. & Bandara, K., Apr 2022, In: Pattern Recognition. 124, 17 p., 108441.

  Research output: Contribution to journal › Article › Research › peer-review
  10 Citations (Scopus)

• LoMEF: a framework to produce local explanations for global model time series forecasts

  Rajapaksha, D., Bergmeir, C. & Hyndman, R. J., 20 Aug 2022, (Accepted/In press) In: International Journal of Forecasting. 24 p.

  Research output: Contribution to journal › Article › Research › peer-review
  1 Citation (Scopus)

• Probabilistic causal effect estimation with global neural network forecasting models

  Grecov, P., Prasanna, A. N., Ackermann, K., Campbell, S., Scott, D. A., Lubman, D. I. & Bergmeir, C., 19 Jul 2022, (Accepted/In press) In: IEEE Transactions on Neural Networks and Learning Systems. 15 p.

  Research output: Contribution to journal › Article › Research › peer-review

• Pruning vs XNOR-Net: A Comprehensive Study of Deep Learning for Audio Classification on Edge-devices

  Mohaimenuzzaman, M., Bergmeir, C. & Meyer, B., 6 Jan 2022, In: IEEE Access. 10, p. 6696-6707 12 p.

  Research output: Contribution to journal › Article › Research › peer-review

  Open Access
  4 Citations (Scopus)
• 2021

  Ensembles of localised models for time series forecasting

  Godahewa, R., Bandara, K., Webb, G. I., Smyl, S. & Bergmeir, C., 5 Dec 2021, In: Knowledge-Based Systems. 233, 17 p., 107518.

  Research output: Contribution to journal › Article › Research › peer-review
  8 Citations (Scopus)

• Improving the accuracy of global forecasting models using time series data augmentation

  Bandara, K., Hewamalage, H., Liu, Y. H., Kang, Y. & Bergmeir, C., Dec 2021, In: Pattern Recognition. 120, 15 p., 108148.

  Research output: Contribution to journal › Article › Research › peer-review
  23 Citations (Scopus)

• LSTM-MSNet: leveraging forecasts on sets of related time series with multiple seasonal patterns

  Bandara, K., Bergmeir, C. & Hewamalage, H., Apr 2021, In: IEEE Transactions on Neural Networks and Learning Systems. 32, 4, p. 1586-1599 14 p.

  Research output: Contribution to journal › Article › Research › peer-review

• SQAPlanner: generating data-informed software quality improvement plans

  Rajapaksha, D., Tantithamthavorn, C., Jiarpakdee, J., Bergmeir, C., Grundy, J. & Buntine, W., 2 Apr 2021, (Accepted/In press) In: IEEE Transactions on Software Engineering. 24 p.

  Research output: Contribution to journal › Article › Research › peer-review
  1 Citation (Scopus)
• 2020

  LoRMIkA: Local Rule-based Model interpretability with k-optimal associations

  Rajapaksha, D., Bergmeir, C. & Buntine, W., Nov 2020, In: Information Sciences. 540, p. 221-241 21 p.

  Research output: Contribution to journal › Article › Research › peer-review
  9 Citations (Scopus)

• Recurrent Neural Networks for time series forecasting: current status and future directions

  Hewamalage, H., Bergmeir, C. & Bandara, K., Jan 2020, In: International Journal of Forecasting. 37, 1, p. 388-427 40 p.

  Research output: Contribution to journal › Article › Research › peer-review
  200 Citations (Scopus)

• Towards accurate predictions and causal 'What-if' analyses for planning and policy-making: a case study in Emergency Medical Services demand

  Bandara, K., Bergmeir, C., Campbell, S., Scott, D. & Lubman, D., 2020, 2020 International Joint Conference on Neural Networks (IJCNN), 2020 Conference Proceedings2020 International Joint Conference on Neural Networks, IJCNN 2020 - Proceedings. Roy, A. (ed.). Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers, 10 p. 9206787

  Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
  3 Citations (Scopus)