Publications

Refereed Journal Papers

  • Pathberiya H. A., Tilakaratne C. D. and Hansen L. L. (2019). An improved algorithm to handle noise objects in hierarchical clustering, International Journal of Data Science, 4(1).
  • Chandrasekara, N. V. Tilakaratne C.D. & Mammadov M.A. (2018). AN ENSEMBLE TECHNIQUE FOR MULTI CLASS IMBALANCED PROBLEM USING PROBABILISTIC NEURAL NETWORKS, Advances and Applications in Statistics, 53(6).
  • Gayan P Withanage, Sameera D Viswakula, YI Nilmini Silva Gunawardena, Menaka D Hapugoda (2018). A forecasting model for dengue incidence in the District of Gampaha, Sri Lanka, Parasites & vectors, 11.
  • Nanthakumaran, P. & Tilakaratne, C. D. (2018). Financial Time Series Forecasting Using Empirical Mode Decomposition and FNN: A Study on Selected Foreign Exchange Rates. ICTer journal 11(1).
  • Tilakaratne, C. D., Mammadov, M. A. & Morris, S. A. (2009). Modified Neural Network Algorithms for Predicting Trading Signals of Stock Market Indices, Journal of Applied Mathematics and Decision Sciences, 2009, Article ID 125308, 22 Pages.
  • Napagoda N. A. D. N., & Tilakaratne, C. D. (2012). Artificial Neural Network Approach for Modelling Soil Temperature: A Case Study for Bathalagoda Area. Sri Lankan Journal of Applied Statistics, 13
  • Pan, H., Tilakaratne, C. & Yearwood, J. (2003). Predicting the Australian Stock Market Index Using Neural Networks Exploiting Dynamical Swings and Intermarket Influences. Lecture Notes in Artificial Intelligence, 2903, 327-338, Springer; Updated version in Journal of Research and Practice in Information Technology, 37(1) (2005).

Refereed Conference Papers

  • Nanthakumaran, P. & Tilakaratne, C. D. (2017). ‘A Comparison of Accuracy of Forecasting Models: A Study on Selected Foreign Exchange Rates’, Proceedings of International Conference on Advances in ICT for Emerging Regions, Colombo, Sri Lanka.
  • Pathberiya H. A., Tilakaratne C. D. & Hansen L. L. (2017). ‘An intelligent decision support system for Forex trading through artificial neural network integrated with GARCH estimates and Intrinsic Mode Functions’, Proceedings of the IEEE Technically Sponsored Intelligent Systems Conference (IntelliSys) 2017, London pp 436-445.
  • Pathberiya H. A., Tilakaratne C. D. & Hansen L. L. (2017). ‘Expert System to Forecast Exchange Rate behaviour towards News Surprises: An application to EUR/USD Exchange Rates’, Proceedings of the International Conference on Computational Modeling & Simulation (ICCMS), Colombo. pp. 23-26.
  • Silva, S. S. M., Tilakaratne, C. D., & Munasinghe, R. (2016). Impact of Day of the Week Effect on All Share Price Index (ASPI) and a Comparison of Forecastability of GARCH and NARX Models, Proceedings of International Conference on Advances in ICT for Emerging Regions, Negambo, Sri Lanka.
  • Rangana, D. L. M., Chandrasekara, N. V., & Tilakaratne, C. D. (2011). Comparison of support vector regression and artificial neural network models to forecast daily price index of the Colombo Stock Excahnge, Proceedings of the International Statistics Conference 2011, Colombo Sri Lanka.
  • Dassanayake, M. M. K., & Tilakaratne, C. (2010). Predicting Trading Signals of Sri Lankan Stock Market Using Genetic Algorithms and Neural Networks, in K. Elleithy et al. Eds. Technological Developments in Networking: Education and Automation, Springer Science+Business Media.
  • Chandrasekara N. V. & Tilakaratne, C. D. (2010). Forecasting Exchange Rates Using Artificial Neural Networks, Proceedings of the International Statistics Conference 2010, Colombo Sri Lanka.
  • Tilakaratne, C. D., Mammadov, M. A. & Morris, S. A. (2008). Predicting Trading Signals of Stock Market Indices Using Neural Networks, In W. Wobcke and M. Zhang Eds., Proceedings of the Twenty First Australian Joint Conference on Artificial Intelligence, Lecture Notes in Artificial Intelligence, 5360, pp 522-531, Springer-Verlag.
  • Tilakaratne, C. D (2008). A Neural Network Approach for the Directional Prediction of a Stock Market: An Application to the Australian All Ordinary Index, Proceedings of the International Research Conference on Management and Finance, Sri Lanka.
  • Tilakaratne, C. D., Tissera, J. H. D. S. P. & Mammadov, M. A. (2008). Predicting Trading Signals of the All Share Price Index Using a Modified Neural Network Algorithm, Proceedings of the 9th International Information Technology Conference, Colombo, Sri Lanka.
  • Tilakaratne, C. D., Mammadov, M. A. & Morris, S. A. (2007). Effectiveness of Using Quantified Intermarket Influence for Predicting Trading Signals of Stock Markets, in P. Christen, P. Kennedy, J. Li, I. Kolvshkina, and G. Williams Ed., Proceedings of the Sixth Australian Data Mining Conference (AusDM 2007), Conferences in Research and Practice in Information Technology (CRPIT), 70, 167-175.
  • Tilakaratne, C. D., Morris, S. A., Mammadov, M.A. & Hurst, C. P. (2007). Predicting Stock Market Index Trading Signals Using Neural Networks, Proceedings of the 14th Annual Global Finance Conference (GFC 2007), Melbourne, Australia.
  • Tilakaratne, C. D., Mammadov, M.A. & Hurst, C. P. (2006). Quantification of Intermarket Influence Based on the Global Optimization and Its Application for Stock Market Prediction, Proceedings of the International Workshop on Integrating AI and Data Mining (AIDM’06), Hobart, Tasmania, Australia.

Refereed Abstracts

  • Pathberiya H. A., Hansen L. L. and Tilakaratne C. D. (2017). ‘Empirical Mode Decomposition and ANN Based Hybrid Approach to Forecast High Frequency Foreign Exchange Rates’, Proceedings of the International Symposium on Forecasting 2017, Cairns, Australia.
  • Dassanayake, N. N. & Tilakaratne, C. D. (2008). Factors influencing the direction of the close price of the all share price index, Proceedings of the University of Colombo Annual Research Symposium, Colombo, Sri Lanka.
  • Tilakaratne, C. D. & Mammadov, M. A. (2008). A new approach for forecasting the direction of stock market indices, Proceedings of the University of Colombo Annual Research Symposium, Colombo, Sri Lanka.