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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