Shrestha, D.L. and Solomatine, D.P. (2006). Experiments with AdaBoost.RT, an improved boosting scheme for regression. Neural Computation, 18(7), pp. 1678-1710. 

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Shrestha, D.L. and Solomatine, D.P. (2006). Machine learning approaches for estimation of prediction interval for the model output. Neural Networks, 19(2), pp. 225-235.

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Solomatine, D., Maskey, M. and Shrestha, D.L. (2008). Instance-based learning compared to other data-driven methods in hydrological forecasting. Hydrological Process, 22(2), pp. 275-287. Full text (pdf).

Shrestha, D.L. and Solomatine, D. (2008). Data-driven approaches for estimating uncertainty in rainfall-runoff modelling. Journal of River Basin Management, 6(2), pp.

109-122. Full text (pdf)

Shrestha, D.L. and Solomatine, D. (2009). A novel method to estimate total model uncertainty using machine learning techniques. Water Resources Research, VOL. 45, W00B11, doi:10.1029/2008WR006839. Full text (pdf)

Shrestha, D.L., Kayastha, N. and Solomatine, D. (2009). A novel approach to parameter uncertainty analysis of hydrological models using neural networks. Hydrology and Earth System Science, 13, pp. 1235-1248, Available on line at: http://www.hydrol-earth-syst-sci.net/13/1235/2009/hess-13-1235-2009.pdf

Shrestha, D.L., Kayastha, N. and Solomatine, D. (2009). Comparison of novel approaches to parameter uncertainty analysis of hydrological models. Hydrological Science Journal,  (Submitted)