Staff profile

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Dr Abbas Khosravi

Position: Senior Research Fellow in Systems Modelling and Soft Computing
role description
Faculty or Division: Office of the Deputy Vice-Chancellor (Research)
Department: Centre for Intelligent Systems Research
Campus: Geelong Waurn Ponds Campus
Phone: +61 3 52272507 +61 3 52272507
Email: abbas.khosravi@deakin.edu.au

Biography

Qualifications

  • Doctor of Philosophy, Deakin University, 2011


Career highlights

2010-present: Research Fellow, Centre for Intelligent Systems Research, Deakin University, Australia
2007-2010: PhD, Deakin University, Australia
2006-2007: Research Fellow, University of Girona, Spain


Affiliations

Alfred Deakin Postdoc Research Fellow


Academic

Expertise summary

Artificial intelligence and Soft computing Optimization Simulation and modeling Forecasting and classification Uncertainty quantification

Awards

Awards and prizes

Vice-Chancellor's Award for Outstanding Contribution to Research: Early Career Researcher, Deakin University, 2012

AlfredAlfred Deakin Postdoctoral Research Fellowship, Deakin University, 2011

Deakin University International Research Scholarship (DUIRS), PhD career, 2007 

Research fellowship from University of Girona for Research on Classification of Electrical Sags, 2006-2007.


Research

Research interests

- Neural networks
- Fuzzy logic systems (type 1 and 2)
- Computational intelligence
- Evolutionary optimisation
- Uncertainty quantification
- Application of AI-based methods for decision-making

Abbas is a reviewer for the following Scholarly Journals:
- IEEE Transactions on Neural Networks
- Neural Networks
- IEEE Transaction on Power Systems


Research grants

Chief Investigator in Discovery Project 2012, funded by Australian Research Council ($270,000 for three years) for conducting fundamental research in the field of artificial intelligence.

Central Research Grant Scheme (CRGS) 2011 funded by Deakin University ($15,000 for one year) for conducting fundamental research in the field of renewable energies and decision-making.


Research page

http://www.deakin.edu.au/research/admin/pubs/reports/database/dynamic/output/person/person.php?person_code=KHOSRAB


Publications

Publications

  1. A. Khosravi, S. Nahavandi, D. Creighton, “Load Forecasting and Neural Networks: A Prediction Interval-Based Perspective”, Studies in Computational Intelligence, Springer Berlin / Heidelberg, Vol. 302, 2010, pp.131-150.
  2. A. Khosravi, J. Melendez, J. Colomer, “Multiway Principal Component Analysis (MPCA) for Upstream/Downstream Classification of Voltage Sags Gathered in Distribution Substations”, Book Series Studies in Computational Intelligence, Springer Berlin / Heidelberg, Vol. 116, 2008, pp. 297-312.
  3. A. Khosravi, S. Nahavandi, “Quantifying Uncertainties Of Neural Network-based Electricity Price Forecasts”, Applied Energy, 2013, Article in Press.
  4. A. Khosravi, S. Nahavandi, “Combined Non-Parametric Prediction Intervals for Wind Power Generation”, IEEE Transactions on Sustainable Energy, 2013, Article in Press.
  5. A. Khosravi, S. Nahavandi, D. Creighton, “Prediction Intervals for Short-Term Wind Farm Power Generation Forecasts”, IEEE Transactions on Sustainable Energy, 2013, Article in Press.
  6. S. Araghi, A. Khosravi, M. Johnstone, D. Creighton, “A Novel Modular Q-Learning Architecture to Improve Performance Under Incomplete Learning in a Grid Soccer Game”, Engineering Applications of Artificial Intelligence, 2013, Article in Press.
  7. A. Khosravi, S. Nahavandi, D. Creighton, “A Neural Network-GARCH-based Method for Construction of Prediction Intervals”, Electric Power Systems Research, Vol. 96, pp. 185-193.
  8. A. Khosravi, S. Nahavandi, D. Creighton, D. Srinivasan, “Interval Type-2 Fuzzy Logic Systems for Load Forecasting: A Comparative Study”, IEEE Transactions on Power Systems, Vol. 27, No. 3, pp. 1274-1282.
  9. A. Khosravi, S. Nahavandi, D. Creighton, “A Comprehensive Review of Neural Network-based Prediction Intervals”, IEEE Transactions on Neural Networks, Vol. 22, No. 9, 2011, pp. 1045-9227.
  10. A. Khosravi, E. Mazloumi, S. Nahavandi, D. Creighton, W. C. van Lint, “A Genetic Algorithm-based Method for Improving Quality Of Travel Time Prediction Intervals”, Transportation Research: Part C Emerging Technologies, Vol. 19, No. 6, 2011, pp. 1364-1376.
  11. A. Khosravi, S. Nahavandi, D. Creighton, “Prediction Intervals to Account for Uncertainties in Travel Time Prediction”, IEEE Transactions on Intelligent Transportation Systems, Vol. 12, No. 3, 2011, pp. 537-547.
  12. A. Khosravi, S. Nahavandi, D. Creighton, “Prediction Interval Construction and Optimization for Adaptive Neuro Fuzzy Inference Systems”, IEEE Transactions on Fuzzy Systems, Vol. 19, No. 5, 2011, pp. 983-988.
  13. A. Khosravi, S. Nahavandi, D. Creighton, A. Atiya, “Lower Upper Bound Estimation Method for Construction of Neural Network-Based Prediction Intervals”, IEEE Transactions on Neural Networks, Vol. 22, No. 3, 2011, pp. 337-346.
  14. A. Khosravi, S. Nahavandi, D. Creighton, “Construction of Optimal Prediction Intervals for Load Forecasting Problem”, IEEE Transactions on Power Systems, Vol. 25, No. 3, 2010, pp. 1496-1503.
  15. A. Khosravi, S. Nahavandi, D. Creighton, “Prediction Interval Construction Using Delta and Bayesian Techniques: A Comparative Study”, Expert Systems with Applications, Vol. 7, No. 3, 15, 2010, pp. 2377-2387.
  16. A. Khosravi, J. Melendez, J. Colomer, “Classification of Sags Gathered in Distribution Substations Based on MPCA”, Electric Power System Research Journal, Vol. 79, No. 1, 2009, pp. 144-151.


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