Publications

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Author Title Type Year(Asc)
2019
Quilty, J., Adamowski, J., & Boucher, M. - A.. (2019). A stochastic data-driven ensemble forecasting framework for water resources: A case study using ensemble members derived from a database of deterministic wavelet-based models. Water Resources Research, 55, 175–202.
Barzegar, R., Ghasri, M., Qi, Z., Quilty, J., & Adamowski, J.. (2019). Using Bootstrap ELM and LSSVM Models to Estimate River Ice Thickness in the Mackenzie River Basin in the Northwest Territories, Canada. Journal of Hydrology. Elsevier.
2018
Quilty, J., & Adamowski, J.. (2018). Addressing the incorrect usage of wavelet-based hydrological and water resources forecasting models for real-world applications with best practices and a new forecasting framework. Journal of hydrology, 563, 336–353. Elsevier.
Quilty, J.. (2018). An Ensemble Wavelet-based Stochastic Data-driven Framework for Addressing Nonlinearity, Multiscale Change, and Uncertainty in Water Resources Forecasting. McGill University Libraries.
Quilty, J., Adamowski, J., Khalil, B., & Rathinasamy, M.. (2018). Information-theoretic-based input variable selection for hydrology and water resources. In EGU General Assembly Conference Abstracts (Vol. 20, p. 2379).
Quilty, J., & Adamowski, J.. (2018). A stochastic data-driven forecasting framework using wavelets for forecasting uncertain hydrological and water resources processes. In EGU General Assembly Conference Abstracts (Vol. 20, p. 2380).
2017
Boucher, M. - A., Quilty, J., & Adamowski, J.. (2017). Hydrological data assimilation using Extreme Learning Machines. In EGU General Assembly Conference Abstracts (Vol. 19, p. 5722).
Deo, R. C., Tiwari, M. K., Adamowski, J. F., & Quilty, J. M.. (2017). Forecasting effective drought index using a wavelet extreme learning machine (W-ELM) model. Stochastic environmental research and risk assessment, 31, 1211–1240. Springer Berlin Heidelberg.
Deo, R. C., Downs, N., Parisi, A. V., Adamowski, J. F., & Quilty, J. M.. (2017). Very short-term reactive forecasting of the solar ultraviolet index using an extreme learning machine integrated with the solar zenith angle. Environmental research, 155, 141–166. Academic Press.
2016
Quilty, J., Adamowski, J., Khalil, B., & Rathinasamy, M.. (2016). Bootstrap rank-ordered conditional mutual information (broCMI): A nonlinear input variable selection method for water resources modeling. Water Resources Research, 52, 2299–2326.
Belayneh, A., Adamowski, J., Khalil, B., & Quilty, J.. (2016). Coupling machine learning methods with wavelet transforms and the bootstrap and boosting ensemble approaches for drought prediction. Atmospheric research, 172, 37–47. Elsevier.
Yaseen, Z. Mundher, Jaafar, O., Deo, R. C., Kisi, O., Adamowski, J., Quilty, J., & El-Shafie, A.. (2016). Stream-flow forecasting using extreme learning machines: A case study in a semi-arid region in Iraq. Journal of Hydrology, 542, 603–614. Elsevier.
2015
Ciupak, M., Ozga-Zielinski, B., Adamowski, J., Quilty, J., & Khalil, B.. (2015). The application of dynamic linear bayesian models in hydrological forecasting: varying coefficient regression and discount weighted regression. Journal of Hydrology, 530, 762–784. Elsevier.
Quilty, J., & Adamowski, J. F.. (2015). Stochastic weather inputs for improved urban water demand forecasting: application of nonlinear input variable selection and machine learning methods. In AGU Fall Meeting Abstracts.
2014
Adamowski, J. F., Quilty, J., Khalil, B., & Rathinasamy, M.. (2014). Forecasting Urban Water Demand via Machine Learning Methods Coupled with a Bootstrap Rank-Ordered Conditional Mutual Information Input Variable Selection Method. In AGU Fall Meeting Abstracts.
Goyal, M. Kumar, Bharti, B., Quilty, J., Adamowski, J., & Pandey, A.. (2014). Modeling of daily pan evaporation in sub tropical climates using ANN, LS-SVR, Fuzzy Logic, and ANFIS. Expert systems with applications, 41, 5267–5276. Elsevier.
2013
Belayneh, A., Adamowski, J., & Khalil, B.. (2013). Forecasting drought via bootstrap and machine learning methods. In CSCE 3rd Specialty Conference on Disaster Prevention and Mitigation.

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