List of Publications Dimitri Solomatine

Books

  • D.P. Solomatine Mathematical and program realization of interactive structural modelling system. VNIISI, Russian Academy of Sciences, Moscow, 1982 (in Russian).

 

PhD Thesis

  • D.P. Solomatine Development and application of the interactive system for structural modelling in management. PhD Thesis, Institute for Systems Studies, Russian Academy of Sciences, Moscow, 1984 (in Russian).

 

Edited volumes, special journal issues 

  • Practical Hydroinformatics: computational intelligence and technological developments in water applications, Edited Volume by Springer (B. Abrahart, L. See, D.P. Solomatine, eds.), 2008.
  • Uncertainty in flood risk management. Special Issue of the J. River Basin Management, 2008, vol. 6(2) (J. Hall, D.P. Solomatine, eds). 
  • Data Driven Modelling and Evolutionary Optimization for River Basin Management. Special Issue of the Journal of Hydroinformatics, 2008, vol 10(1) (A. Ostfeld, D.P. Solomatine, eds).
  • Hydroinformatics: computational intelligence and technological developments in hydrologic applications. Special Issue of the Hydrological Sciences Journal, 2007 (B. Abrahart, L. See, D.P. Solomatine, E. Toth, eds).
  • Hydroinformatics: computational intelligence and technological developments in water science applications, Special Issue of the Hydrology and Earth Systems Sciences, 2007 (B. Abrahart, L. See, D.P. Solomatine, E. Toth, eds).
  • Computational Intelligence in Earth and Environmental Sciences. Special Issue of the Neural Networks Journal, 2007, vol. 20(4), (V. Cherkassky, W. Hsieh, V. Krasnopolsky, D.P. Solomatine, J. Valdes, eds.).
  • Earth Sciences and Environmental Applications of Computational Intelligence. Special Issue of the Neural Networks Journal, 2006, vol. 19(2), (V. Cherkassky, V. Krasnopolsky, D.P. Solomatine, J. Valdes, eds.).

 

Papers in peer-reviewed journals

  • Delipetrev B., Jonoski A., Solomatine D.P. Development of a web application for water resources based on open source software, Computers & Geosciences, 62, January 2014, 35-42. 
  • M. Nasseri, B. Zahraie, A. Ansari and D. P. Solomatine (2013). Uncertainty assessment of monthly water balance models based on Incremental Modified Fuzzy Extension Principle method. J. Hydroinformatics, 15(4), 1340–1360, doi: 10.2166/hydro.2013.159. 
  • Almoradie A., Jonoski A., Popescu I. and Solomatine D. (2013) Web-based access to water-related data using OGC WaterML 2.0. Int. J. of Advanced Computer Science and Applications (accepted).
  • Almoradie, A., Jonoski, A., Stoica, F., Solomatine, D.P., Popescu, I. (2013). Web-based flood information system: case study of Somesul-Mare, Romania, J. Environmental Engineering and Management, 12(5), 1065-1070. 
  • V. Moya Quiroga, I. Popescu, D.P. Solomatine, L. Bociort (2013). Cloud and cluster computing in uncertainty analysis of integrated flood models. J. Hydroinformatics, 15(1), 55-69, online on 18 July 2012, doi:10.2166/hydro.2012.017. 
  • R. J. Abrahart, F. Anctil, P. Coulibaly, C. W. Dawson, N. J. Mount, L. M. See, A. Y. Shamseldin, D. P. Solomatine, E. Toth, R. L. Wilby. Two decades of anarchy? Emerging themes and outstanding challenges for neural network river forecasting. Progress in Physical Geography, August 2012, 36(4), 480-513, online on July 2012, doi: 10.1177/0309133312444943. 
  • Bhattacharya, B., van Kessel, T. and Solomatine, D.P. Spatio-temporal prediction of suspended sediment concentration in the coastal zone using artificial neural network and a numerical model. J. of Hydroinformatics, 14(3), 574-594, 2012. 
  • Gichamo Z., G., Popescu, I., Jonoski, A.,  Solomatine, D.P. River Cross Section Extraction from ASTER Global DEM for Flood Modeling, Environmental Modelling & Software, 31(5), 37-46, 2012. 
  • Di Baldassarre, G., Elshamy, M., van Griensven, A., Soliman, E., Kigobe, M., Ndomba, P., Mutemi, J., Mutua, F., Moges, S., Xuan, J.-Q., Solomatine, D. & Uhlenbrook, S. Future hydrology and climate in the River Nile basin: a review. Hydrol. Sci. J. 56(2), 2011, 199-211. 
  • Siek, M.B. and Solomatine, D.P. Real-time Data Assimilation for Chaotic Storm Surge Model Using NARX Neural Network. Journal of Coastal Research, SI 64, 1184-1188, 2011.
  • Siek, M.B. and Solomatine, D.P. Optimized Dynamic Ensembles of Multiple Chaotic Models in Predicting Storm Surges. Journal of Coastal Research, SI 64, 1189-1194, 2011.
  • M. Siek and D. P. Solomatine. Nonlinear chaotic model for predicting storm surges. Nonlinear Processes in Geophysics, 17, 405–420, 2010. 
  • K. Hassaballah, A. Jonoski, I. Popescu, D.P. Solomatine. Model-Based Optimization of Downstream Impact During Filling of a New Reservoir: Case Study of Mandaya/Roseires Reservoirs on the Blue Nile River. Water Resources Management, DOI: 10.1007/s11269-011-9917-8, 2011. 
  • Jung, N. C., Popescu, I., Price R. K., Solomatine,  D., Kelderman, P.,  Shin, J.K. (2011), The use of the A.G.P. test for determining the phytoplankton production and distribution in the thermally stratified reservoirs: The case of the Yongdam reservoir in Korea.  J. of Environmental Engineering and Management, 10 (11), 1647-1657. 
  • A. Elshorbagy, G. Corzo, S. Srinivasulu, and D.P. Solomatine. Experimental investigation of the predictive capabilities of data driven modeling techniques in hydrology - Part 1: Concepts and methodology. Hydrol. Earth Syst. Sci., 14, 1931–1941, 2010. 
  • A. Elshorbagy, G. Corzo, S. Srinivasulu, and D.P. Solomatine. Experimental investigation of the predictive capabilities of data driven modeling techniques in hydrology - Part 2: Application. Hydrol. Earth Syst. Sci., 14, 1943–1961, 2010.
  • W. Barreto, Z. Vojinovic, R.K. Price, D.P. Solomatine. A multi-objective evolutionary approach to rehabilitation of urban drainage systems. ASCE Journal of Water Resources Planning and Management, 2010, doi: 10.1061/(ASCE)WR.1943-5452.0000070.
  • L. Alfonso, A. Jonoski, D.P. Solomatine. Multi-objective optimisation of operational responses for contaminant flushing in water distribution networks. ASCE Journal of Water Resources Planning and Management, 136 (1), 2010, 48-58, doi: 10.1061/(ASCE)0733-9496(2010)136:1(48). 
  • Jung, N.C,  Popescu, I.,  Kelderman, P., Solomatine, D.P. and Price, R.K. Application of model trees and other machine learning techniques for algal growth prediction in Yongdam reservoir, Republic of Korea. J. of Hydroinformatics, 12(3), 2010, 262–274, doi:10.2166/hydro.2009.004. 
  • A. Zamani, A. Azimian, A. Heemink, D.P. Solomatine. Non-linear wave data assimilation with an ANN-type wind-wave model and Ensemble Kalman Filter (EnKF). Applied Mathematical Modelling (2009), doi:10.1016/j.apm.2009.10.013. 
  • G. Corzo, D. Solomatine, Hidayat, M. de Wit, M. Werner, S. Uhlenbrook, and R. Price. Combining semi-distributed process-based and data-driven models in flow simulation: a case study of the Meuse river basin. Hydrol. Earth Syst. Sci., 13, 1619–1634, 2009. 
  • D. L. Shrestha, N. Kayastha, and D. P. Solomatine. A novel approach to parameter uncertainty analysis of hydrological models using neural networks. Hydrol. Earth Syst. Sci., 13, 1235–1248, 2009. 
  • D.P. Solomatine, D.L. Shrestha. A novel method to estimate model uncertainty using machine learning techniques. Water Resources Res. 45, W00B11, doi:10.1029/2008WR006839, 2009. 
  • A. Zamani, A. Heemink, A. Azimian, D.P. Solomatine. Wave height prediction at Caspian Sea using data driven model and ensemble based data assimilation methods, J. Hydroinformatics, 2009, 11(2), 154–164. 
  • A. Zamani, D.P. Solomatine, A. Azimian, A. Heemink. Learning from data for wind–wave forecasting. Ocean Engineering, 2008, 35(10), 953-962. 
  • J. Hall, D.P. Solomatine. A framework for uncertainty analysis in flood risk management decisions. J. River Basin Management, 2008, 6(2), 85-98.
  • D.L. Shrestha, D.P. Solomatine. Data-driven approaches for estimating uncertainty in rainfall-runoff modelling. J. River Basin Management, 2008, 6(2), 109-122.
  • D.P. Solomatine and A. Ostfeld. Data-driven modelling: some past experiences and new approaches. J of Hydroinformatics, 2008, 10(1), 3-22. 
  • W. Nishida, D.P. Solomatine, M. Noguchi and S. Suzuki. Model parameter estimation by global optimization algorithm ACCO complemented by an ANN-based error estimator. JSCE Ann. J. of Hydraulic Engineering, 52, 2008, 1411-1416 (in Japanese). 
  • Fenicia, F., Solomatine, D. P., Savenije, H. H. G. and Matgen, P. Soft combination of local models in a multi-objective framework. Hydrol. Earth Syst. Sci., 11, 1797-1809, Special Issue “Data-driven approaches, optimization and model integration: hydrological applications”, R. Abrahart, L. See, D. Solomatine, and E. Toth (eds.), 2007. 
  • G. Corzo and D.P. Solomatine. Baseflow separation techniques for modular artificial neural network modelling in flow forecasting. Hydrological Sciences J., 2007, 52(3), 491-507.
  • L. See, D.P. Solomatine, R. Abrahart, and E. Toth. Hydroinformatics: computational intelligence and technological developments in water science applications. Hydrological Sciences J., 2007, 52(3), 391-396. 
  • G. Corzo and D.P. Solomatine. Knowledge-based modularization and global optimization of artificial neural network models in hydrological forecasting. Neural Networks, 2007, 20, 528–536. 
  • D.P. Solomatine, M. Maskey, D.L. Shrestha. Instance-based learning compared to other data-driven methods in hydrologic forecasting. Hydrological Processes, 2008, 22, 275 – 287 (first published online: 24-July, 2007). 
  • Bhattacharya, B., Price, R.K., and D.P. Solomatine. A machine learning approach to modelling sediment transport, ASCE J. of Hydraulic Engineering, 2007, 133(4), 440-450. 
  • Vojinovic, Z.; Solomatine, D. and Price, R. K. Dynamic least-cost optimization of waste water systems remedial works requirements. Water, Science and Technology, 2006, 54(6-7), 467-475.
  • D.L. Shrestha, D.P. Solomatine. Experiments with AdaBoost.RT, an Improved Boosting Scheme for Regression. Neural Computation, 2006, 17, 1678-1710. 
  • D.L. Shrestha, D.P. Solomatine. Machine learning approaches for estimation of prediction interval for the model output. Neural Networks J., 2006, 19(2), 225-235.
  • D.P. Solomatine, M.B. Siek. Modular learning models in forecasting natural phenomena. Neural Networks J., 2006, 19(2), 215-224.
  • B. Bhattacharya, D.P. Solomatine. Machine learning in sedimentation modeling. Neural Networks J., 2006, 19(2), 208-214.
  • B. Bhattacharya, D.P. Solomatine. Machine learning in soil classification. Neural Networks J., 2006, 19(2), 186-195. 
  • V. Cherkassky, V. Krasnopolsky, D.P. Solomatine, J. Valdes. Computational Intelligence in Earth Sciences and Environmental Applications: Issues and Challenges. Neural Networks J., 2006, 19(2), 113-121.
  • B. Bhattacharya, R.K. Price and D.P. Solomatine. Data-driven modelling in context to sediment transport. Journal of Physics and Chemistry of the Earth, Parts A/B/C, 30 (4-5), 2005, 297-302. 
  • W. Nishida, M. Noguchi, D.P. Solomatine. Study on Numerical Prediction of Tidal Current using Forecasted Weather Data. JSCE Ann. J. of Hydraulic Engineering, 2005, 49(2), 1279-1284 (in Japanese). 
  • B. Bhattacharya and D.P. Solomatine. Neural networks and M5 model trees in modelling water level-discharge relationship. Neurocomputing, 63, 2005, 381-396. 
  • A.H. Lobbrecht, Y. Dibike and D.P. Solomatine. Artificial Neural Networks and Fuzzy Systems in Model Based Control of the Overwaard Polder. ASCE Journal of Water Resources Planning and Management, 131(2), 2005, 135-145. 
  • D.P. Solomatine and Y. Xue. M5 model trees compared to neural networks: application to flood forecasting in the upper reach of the Huai River in China. ASCE Journal of Hydrologic Engineering, 9(6), 2004, 491-501. 
  • W. Nishida, M. Noguchi, H. Matsushita and D.P. Solomatine. A Study on the Application of Genetic Algorithm to Calibration of Water Quality Model. Ann. J. of Hydraulic Engineering, 48 (2), 2004, 1321-1326 (in Japanese). 
  • M. Noguchi, D.P. Solomatine, W. Nishida. Automatic Calibration of Water Quality Simulation Model Using Global Optimization Technique, Ann. J. of Hydraulic Engineering, 47 (2), 2003, 1267-1272 (in Japanese). 
  • B. Bhattacharya, A.H. Lobbrecht, D.P. Solomatine. Neural networks and reinforcement learning in control of water systems. ASCE Journal of Water Resources Planning and Management, vol. 129 (6), 2003, 458-465. 
  • D.P. Solomatine, K.N. Dulal. Model trees as an alternative to neural networks in rainfall–runoff modelling. Hydrological Sciences Journal, 48(3), 2003, 399-411. 
  • A.H. Lobbrecht, D.P. Solomatine. Machine learning in real-time control of water systems. Urban Water, 4, 2002, 283-289.
  • S. Maskey, A. Jonoski, D.P. Solomatine. Groundwater remediation strategy using global optimization algorithms. ASCE Journal of Water Resources Planning and Management, 128 (6), 2002, 431-440.
  • Y.B. Dibike, S. Velickov ., D.P. Solomatine and M.B. Abbott. Model induction with support vector machines: introduction and applications. ASCE Journal of Computing in Civil Engineering, 15(3), 2001, 208-216.
  • Y.B. Dibike and D.P. Solomatine. River Flow Forecasting Using Artificial Neural Networks, Journal of Physics and Chemistry of the Earth, Part B: Hydrology, Oceans and Atmosphere, 26(1), 2001, 1-8.
  • A.J. Abebe, D.P. Solomatine, R. Venneker. Application of adaptive fuzzy rule-based models for reconstruction of missing precipitation events. Hydrological Sciences Journal, 45(3), 2000, 425-436.
  • H. Yan, D.P. Solomatine, S. Velickov, M.B. Abbott. Distributed environmental impact assessment using Internet. Journal of Hydroinformatics, 1(1). 1999, 59 70.
  • D.P. Solomatine, Y. Dibike, N. Kukuric. Automatic calibration of groundwater models using global optimization techniques. Hydrological Sciences Journal, 44(6), 1999, 879-894.
  • Y.B. Dibike, D.P. Solomatine, M.B. Abbott. On the encapsulation of numerical-hydraulic models in artificial neural network. Journal of Hydraulic Research, 2, 1999, 147-161.
  • D.P. Solomatine. Two strategies of adaptive cluster covering with descent and their comparison to other algorithms. Journal of Global Optimization, 14(1), 1999, 55-78.
  • Y. Shen, D.P. Solomatine, H. van den Boogaard. Improving performance of chlorophyll concentration time series simulation with artificial neural networks. JSCE Annual Journal of Hydraulic Engineering, 42, 1998, February, 751-756.
  • D.P. Solomatine. Object orientation in hydraulic modelling architectures. ASCE Journal of Computing in Civil Engineering, 10(2), 1996, 125-135.
  • M.B. Abbott, D.P. Solomatine, A.W. Minns, A. Verwey, and W. van Nievelt. Education and training in hydroinformatics. Journal of Hydraulic Research, 32 (extra issue), 1994, 203-214.
  • D.P. Solomatine. PC based tools for building decision support systems: analytical survey. Achievements and Perspectives (issue 46), Management and Progress of Science and Technology Series, No.8, Moscow: International Centre for Scientific and Technological Information, 1986 (in Russian).
  • D.P. Solomatine. Application of structural modelling to regional development management. Achievements and Perspectives (issue 44), Regional Systems Series, No.4, Moscow: International Centre for Scientific and Technological Information, 1985, 115-119.
  • I.A.Ganin,  D.P. Solomatine. Possibilities for formalization of computer models synthesis in management. - Achievements and Perspectives (issue 42), Management and Progress of Science and Technology Series, No.8 - Moscow: International Centre for Scientific and Technological Information, 1984, 80-89.

 

Papers in review at peer-reviewed journals 

  • B. Bhattacharya, T. van Kessel, J. de Kok, D.P. Solomatine. Fine sediment transport modelling of the Dutch coast by combining numerical and data-driven techniques. Continental Shelf Research (submitted). 

 

Chapters in books

  • D. P. Solomatine and T. Wagener. Hydrological Modelling (Chapter 2.16). In: Treatise on Water Science (Wilderer, ed.), Volume 2: The Science of Hydrology, 435-457. Elsevier, 2011.
  • Solomatine, D.P., Abrahart, R., See L. (2008). Data-driven modelling: concept, approaches, experiences. In: Practical Hydroinformatics: Computational Intelligence and Technological Developments in Water Applications (Abrahart, See, Solomatine, eds), Springer-Verlag.
  • Solomatine, D.P., Vojinovic, Z.. (2008). Randomized search optimization algorithms and their application in rehabilitation of urban drainage systems. In: Practical Hydroinformatics: Computational Intelligence and Technological Developments in Water Applications (Abrahart, See, Solomatine, eds), Springer-Verlag.
  • Solomatine, D.P. (2008). Committees of models in hydrologic modelling: boosting, mixtures and trees. In: Practical Hydroinformatics: Computational Intelligence and Technological Developments in Water Applications (Abrahart, See, Solomatine, eds), Springer-Verlag.
  • B. Bhattacharya, I.K. Deibel, S.A.M. Karstens, D.P.Solomatine. Neural Networks in Sedimentation Modelling for the Approach Channel of the Port of Rotterdam. In: Estuarine and Coastal Fine Sediments Dynamics, volume 8, INTERCOH 2003, J. Maa, L. Sanford, D. Schoellhamer (eds.). Elsevier, 2006. 
  • D.P. Solomatine. Data-driven modelling and computational intelligence methods in hydrology. Encyclopedia of Hydrological Sciences (M.G. Andersen, ed), vol. 1, John Wiley & Sons, 2005. 
  • D.P. Solomatine. Applications of data-driven modelling and machine learning in control of water resources. In: Computational intelligence in control, M. Mohammadian, R.A. Sarker and X. Yao (eds.). Idea Group Publishing, 2002, pp. 197 – 217. 
  • S. Velickov, D.P. Solomatine. Predictive data mining: practical examples. In: AI methods in Civil Engineering Applications (O. Schleider, A. Zijderveld, eds). Cottbus, 2000, pp. 3-19.
  • S.Maskey, Y.B. Dibike, A.Jonoski, and D.P. Solomatine. Groundwater model approximation with artificial neural network for selecting optimal pumping strategy for plume removal, In: AI methods in Civil Engineering Applications (O. Schleider, A. Zijderveld, eds), Cottbus, 2000, pp. 67-80.
  • Y.B. Dibike, S. Velickov, D.P. Solomatine. Support vector machines: review and applications in civil engineering. In: AI methods in Civil Engineering Applications 
  • (O. Schleider, A. Zijderveld, eds). Cottbus, 2000, p.45-58.
  • D.P. Solomatine. Random search methods in model calibration and pipe network design. In: Water Industry Systems: Modelling and Optimization Applications, D. Savic, G. Walters (eds.). Research Studies Press Ltd., 1999, pp. 317 332.
  • A.H. Lobbrecht, D.P. Solomatine. Control of water levels in polder areas using neural networks and fuzzy adaptive systems. In: Water Industry Systems: Modelling and Optimization Applications, D. Savic, G. Walters (eds.). Research Studies Press Ltd., 1999, pp. 509 518.
  • V.A. Bogomolov, D.P. Solomatine. The possibilities of expert problem analysis in improving management effectiveness. In: The issues of improving the management of national economy (V.D. Rudashevsky, ed), pp. 90-97. - VNIISI, Moscow, 1987 (in Russian). 
  • V.A. Bogomolov, D.P. Solomatine, R.L. Sheinin. Dialogue software complex for analysis and modelling of organisational systems. In: The issues of organizational system functioning analysis (B.Z. Milner, R.L. Sheinin, eds), pp. 30-44. - VNIISI, Moscow, 1986 (in Russian).
  • D.P. Solomatine. Implementation of decision support systems: the possibilities of using personal computers. - In: Systems and methods for decision support (S.V. Emeljanov, O.I. Larichev, eds), pp. 113-120. - VNIISI, Moscow, 1986 (in Russian). 
  • D.P. Solomatine. Issues and prospects for automating management processes. - In: Modern Issues of Information Technologies (D.S. Chereshkine, ed.). - VNIISI, Moscow, 1986 (in Russian).
  • D.P. Solomatine, A.N. Shvetsov. Goals analysis of the management system in service sector. - In: Issues of organizational systems analysis (B. Milner and R. Sheinin, eds.), pp. 63-73. - VNIISI, Moscow, 1986 (in Russian).
  • I.A.Ganin, A.I. Mishin, D.P. Solomatine. Problem structurization for regional management in a dialogue with a computer. - In: Methods of complex systems analysis, 116-122. - VNIISI, Moscow, 1984 (in Russian).
  • I.A.Ganin, D.P. Solomatine. Structural models in inter-sectoral management: typology and problems of construction. - In: Intersectoral complexes: strategies for development and management (A.V.Kochetkov, ed.), 72-81. VNIISI, Moscow, 1983 (in Russian).
  • K.G. Perfiljev, D.P. Solomatine, L.P. Victorov. Software for integrated system for interactive modelling of complex objects. - In: Software for optimization systems, 57-65. VNIISI, Moscow, 1982 (in Russian).
  • A.A. Petrov, D.P. Solomatine. On possibilities of using interactive computer-based structural modelling methods in analysing the system of decisions in a national plan. - In: Methods of complex systems analysis, 115-122. - VNIISI, Moscow, 1981 (in Russian).
  • D.P. Solomatine. Decisions in economic planning: computer modelling. - In: Regional management (A.V. Kochetkov, ed). - VNIISI, Moscow, 1981 (in Russian).
  • I.A.Ganin, D.P. Solomatine. Complex systems structuring: psychological aspects. - In: Models and methods of systems studies, Part 3 (A. Danilov-Daniljan, ed.) – VNIISI, Moscow, 1981 (in Russian).
  • I.A.Ganin, D.P. Solomatine. Large scale systems structural models: computer development. - In: Issues of management in technology, economics, biology, 129-134. - Nauka publishing house, Moscow, 1981 (in Russian).
  • I.A.Ganin, D.P. Solomatine. Issues of building complex systems structures in a dialogue with a computer. - In: Issues of cybernetics and electronics, pp. 24-29 - Moscow, MAI, 1980 (in Russian).

 

Peer-reviewed conference papers

  • Siek, M.B. and Solomatine, D.P. Nonlinear Multi-model Ensemble Prediction Using Dynamic Neural Network with Incremental Learning. Proc. IEEE International Joint Conferences on Neural Networks, San Jose, USA, July 2011 (Best Student Presentation Award).
  • Siek, M.B. and Solomatine, D.P. Predicting Ocean Surge: Optimized Ensembles of Data Driven Chaos-based Models in Phase Space. Proc. 34th IAHR World Congress, Brisbane, Australia, July 2011. 
  • B. Bhattacharya, S. Sewagudde, T. van Kessel and D.P. Solomatine. A hybrid approach in combining numerical and data-driven models in modelling fine sediment transport. Proc. 34th IAHR World Congress, Brisbane, Australia, 2011.
  • M.B.A. Siek, D.P. Solomatine. Phase error correction for chaotic storm surge model. Proc. 9th Intern. Conf. on Hydroinformatics, Tianjin, China, September 2010. 
  • M.B.A. Siek, D.P. Solomatine. A mixture of multi-models in phase space reconstruction. Proc. 9th Intern. Conf. on Hydroinformatics, Tianjin, China, September 2010. 
  • D. L. Shrestha and D. P. Solomatine. Ranking of Pareto solutions in multi-objective model calibration and uncertainty analysis. Proc. 9th Intern. Conf. on Hydroinformatics, Tianjin, China, September 2010.
  • V. Moya, I. Popescu, D.P. Solomatine. Monte carlo uncertainty analysis of hydraulic models using cloud computing. Proc. 9th Intern. Conf. on Hydroinformatics, Tianjin, China, September 2010.
  • A. D. Santos Almoradie, A. Jonoski, Y. Xuan, T. Gichamo, D.P. Solomatine, J. De Ruiter. Web-based solutions for flood risk analysis, modelling and management. Proc. 9th Intern. Conf. on Hydroinformatics, Tianjin, China, September 2010.
  • N. Kayastha, D. L. Shrestha and D. P. Solomatine. Experiments with several methods of parameter uncertainty estimation in hydrological modeling. Proc. 9th Intern. Conf. on Hydroinformatics, Tianjin, China, September 2010.
  • Z. Xu, C. Velez, D.P. Solomatine, A. Lobbrecht. Use of cloud computing for optimal design of urban wastewater systems. Proc. 9th Intern. Conf. on Hydroinformatics, Tianjin, China, September 2010.
  • B. Bhattacharya, D.P. Solomatine, T. van Kessel. Surrogate modelling of suspended sediment concentration. Proc. 9th Intern. Conf. on Hydroinformatics, Tianjin, China, September 2010.
  • Siek, M.B. and Solomatine, D. P. Predicting Storm Surges: Multi-models, Computational Intelligence, Chaos, Uncertainty. Exploring Complex Dynamics in High-Dimensional Chaotic Systems: From Weather Prediction to Oceanic Flows, Dresden, Germany, January 2010. 
  • M.B.A. Siek, D.P. Solomatine. Multi-model Ensemble Forecasting in High Dimensional Chaotic System. Proc. Int. Joint Conf. on Neural Networks, Barcelona, Spain, July 2010 (Best Student Presentation Award).
  • F. Pianosi, D. L. Shrestha, D. P. Solomatine. ANN-based Representation of Parametric and Residual Uncertainty of Models. Proc. Int. Joint Conf. on Neural Networks, Barcelona, Spain, July 2010. 
  • D. L. Shrestha, N. Kayastha, and D. P. Solomatine. Parametric uncertainty estimation of a hydrological model using piece-wise linear regression surrogates. Proc XXXIII IAHR Congress, Vancouver, Canada, August 2009. 
  • D. L. Shrestha, N. Kayastha, and D. P. Solomatine. ANNs and Other Machine Learning Techniques in Modelling Models’ Uncertainty. Proc. Int. Conf. on Artificial Neural Networks (ICANN), Limassol, Cyprus, September 2009. 
  • M. Siek, D.P. Solomatine. Chaotic Model with Data Assimilation Using NARX Network. Proc. Intern. Joint Conf. on Neural Networks (IJCNN), Atlanta, USA, June 2009. 
  • G. Corzo, A. Jonoski, G. Yimer, Y. Xuan, D.P. Solomatine. Downscaling global climate models using modular models and fuzzy committees. Proc. 8th Intern. Conf. on Hydroinformatics, Concepcion, Chile, January 2009.
  • M. Siek, D.P. Solomatine. Phase-space dimensionality reduction in building storm surge prediction model. Proc. 8th Intern. Conf. on Hydroinformatics, Concepcion, Chile, January 2009.
  • A. Adel, D.L. Shrestha, A. van Griensven, D.P. Solomatine. Comparison of calibration and uncertainty analysis methods: case study of Nzoia river SWAT model. Proc. 8th Intern. Conf. on Hydroinformatics, Concepcion, Chile, January 2009. 
  • W. Barreto, Z. Vojinovic, R.K. Price, D.P. Solomatine. A multi-criteria platform for the rehabilitation of urban drainage systems. Proc. 8th Intern. Conf. on Hydroinformatics, Concepcion, Chile, January 2009. 
  • D.L. Shrestha, N. Kayastha, D.P. Solomatine. Encapsulation of Monte-Carlo uncertainty analysis results in a predictive machine learning model. Proc. 8th Intern. Conf. on Hydroinformatics, Concepcion, Chile, January 2009. 
  • M. Siek, D.P. Solomatine, S. Velickov. Multivariate Chaotic Models vs Neural Networks in Predicting Storm Surge Dynamics. Proc. World Congress of Computational Intelligence, IEEE, Hong Kong, 2008.
  • Siek, M.B., Solomatine, D. P. and Verlaan, M. Short-term Prediction Storm Surges in the North Sea Using Multivariate Chaotic Model. The EuroGOOS Conference: Coastal to Global Operational Oceanography: Achievements and Challenges, Exeter, UK, May 2008.
  • D.L. Shrestha, D.P. Solomatine. Comparing Machine Learning Methods in Estimation of Model Uncertainty. Proc. World Congress of Computational Intelligence, IEEE, Hong Kong, 2008. 
  • W. Barreto, Z. Vojinovic, R.K. Price, D.P. Solomatine. Multi-tier Modelling of Urban Drainage Systems: Muti-objective Optimization and Parallel Computing. 11th International Conference on Urban Drainage, Edinburgh, Scotland, UK, 2008.
  • D.P. Solomatine. Data-driven modelling: experiences and new approaches. Proc. Workshop on Hydroinformatics (HIW-2007), June 2007, Niagara-Falls, Canada. 
  • Siek, M.B. and Solomatine, D. P. Recurrence Plots in the Analysis of Extreme Ocean Storm Surges. Proc. 2nd International Workshop on Recurrence Plots, Siena, Italy, September 2007.
  • D.L. Shrestha, D.P. Solomatine. Predicting hydrological models uncertainty: use of machine learning. Proc XXXII IAHR Congress, Venice, 2007. 
  • G. Corzo, M.B.A. Siek, R.K. Price, and D.P. Solomatine. Modular data-driven hydrologic models with incorporated knowledge: neural networks and model trees. Proc XXXII IAHR Congress, Venice, 2007. 
  • W. Nishida, D.P. Solomatine, M. Noguchi. Numerical simulation of tidal current of Shimabara bay using the forecasted weather data. Proc. 7th Intern. Conf. on Hydroinformatics, Nice, 2006, Research Publishing, 1755-1762. 
  • R.K. Price, I. Popescu, A. Jonoski, and D.P. Solomatine. Fifteen years of experience in hydroinformatics at IHE Delft Institute for Water Education. Proc. 7th Intern. Conf. on Hydroinformatics, Nice, 2006, Research Publishing, 3101-3108. 
  • R.K. Price, W.A. Yohan Fernando, D.P. Solomatine. Inverse modelling for flood propagation. Proc. 7th Intern. Conf. on Hydroinformatics, Nice, Research Publishing, 2006. 
  • Chen, C., Shrestha, D.L., Corzo Perez, G.A., Solomatine, D.P. Comparison of Methods for uncertainty analysis of hydrologic models. Proc. 7th Intern. Conf. on Hydroinformatics, Nice, 2006, Research Publishing, 1309-1316.
  • W. Barreto Cordero, R.K. Price, D.P. Solomatine, Z. Vojinovic. Approaches to multi-objective multi-tier optimization in urban drainage planning. Proc. 7th Intern. Conf. on Hydroinformatics, Nice, Research Publishing, 2006. 
  • X. Liu and D.P. Solomatine. Generation of flood inundation map from remote sensing images: use of neural networks. Proc. 7th Intern. Conf. on Hydroinformatics, Nice, 2006, Research Publishing, 2247-2254.
  • D.L. Shrestha, J. Rodriguez, R.K. Price, D.P. Solomatine. Assessing model prediction limits using fuzzy clustering and neural networks. Proc. 7th Intern. Conf. on Hydroinformatics, Nice, 2006, Research Publishing. 
  • B. Bhattacharya, R.K. Price and D.P. Solomatine. An approach to assess uncertainty of sediment transport models. Proc. 7th Intern. Conf. on Hydroinformatics, Nice, 2006, Research Publishing.
  • G. Corzo Perez, D.P. Solomatine. Optimization of baseflow separation algorithm for modular data-driven hydrologic models. Proc. 7th Intern. Conf. on Hydroinformatics, Nice, 2006, Research Publishing. 
  • D.P. Solomatine, M. Maskey, and D.L. Shrestha. Eager and Lazy Learning Methods in the Context of Hydrologic Forecasting. Proc. Intern. Joint Conf. on Neural Networks, Vancouver, 2006. 
  • D.P. Solomatine and G.A. Corzo. Learning hydrologic flow separation algorithm and local ANN committee modeling. Proc. Intern. Joint Conf. on Neural Networks, Vancouver, 2006.
  • B. Bhattacharya, and D.P. Solomatine. Improving Empirical Models with Machine Learning. Proc. Intern. Joint Conf. on Neural Networks, Vancouver, 2006.
  • D.L. Shrestha, D.P. Solomatine. Quantifying uncertainty of flood forecasting using data driven models. Proc. XXXI IAHR Congress, Seoul, Korea, 2005.
  • D.P. Solomatine. Local parsimonious data-driven models in streamflow forecasting. Proc. XXXI IAHR Congress, Seoul, Korea, 2005.
  • Bhattacharya, B., Price, R.K., and D.P. Solomatine. An improvement of the sediment transport model of Engelund and Hansen, Proc. XXXI IAHR Congress, Seoul, Korea, 2005. 
  • B. Bhattacharya, I.K. Deibel, R.K. Price, D.P. Solomatine. Modelling harbour sedimentation: new paradigms, Proc. of the Conf. Of Maritime and Port Development, Rotterdam, 2005. 
  • D.P. Solomatine. Adaptive cluster covering and evolutionary approach: comparison, differences and similarities. Proc. IEEE Congress on Evolutionary Computation, Edinburgh, U.K., 2005, 1959-1966.
  • D.P. Solomatine. Local and Hybrid Learning Models in Forecasting Natural Phenomena. Proc. Int. Joint Conf. on Neural Networks, Montreal, 2005.
  • D.L. Shrestha and D.P. Solomatine. Estimation of Prediction Intervals for the Model Outputs Using Machine Learning. Proc. Int. Joint Conf. on Neural Networks, Montreal, 2005. 
  • B. Bhattacharya and D.P. Solomatine. Modelling Harbour Sedimentation Using ANN and M5 Model Trees. Proc. Int. Joint Conf. on Neural Networks, Montreal, 2005. 
  • B. Bhattacharya and D.P. Solomatine. Machine Learning in Soil Classification. Proc. Int. Joint Conf. on Neural Networks, Montreal, 2005. 
  • D.P. Solomatine. Experiences in using evolutionary and non-evolutionary optimization methods in models calibration. Proc. of the iEMSs 3rd Biennial Meeting: "Summit on Environmental Modelling and Software" (A. Voinov, A. Jakeman, A. Rizzoli, eds.), Burlington, USA, July 2006. 
  • D.P. Solomatine. Optimal modularization of learning models in forecasting environmental variables. Proc. of the iEMSs 3rd Biennial Meeting: "Summit on Environmental Modelling and Software" (A. Voinov, A. Jakeman, A. Rizzoli, eds.), Burlington, USA, July 2006. 
  • D.L. Shrestha and D.P. Solomatine. A Novel Method to Estimate the Model Uncertainty Based on the Model Errors. Proc. of the iEMSs 3rd Biennial Meeting: "Summit on Environmental Modelling and Software" (A. Voinov, A. Jakeman, A. Rizzoli, eds.), Burlington, USA, July 2006. 
  • M.B. Siek and D. P. Solomatine. Optimizing mixtures of local experts in tree-like regression models. Proc. IASTED Conference on Artificial Intelligence and Applications, M.H. Hamza, (ed), Innsbruck, Austria, February 2005, 497-502.
  • D. P. Solomatine and M.B. Siek. Semi-optimal Hierarchical Regression Models and ANNs. Proc. Intern. Joint Conference on Neural Networks, Budapest, Hungary, July 2004, 1173-1177.
  • D.P. Solomatine and D.L. Shrestha. AdaBoost.RT: a Boosting Algorithm for Regression Problems. Proc. Intern. Joint Conference on Neural Networks, Budapest, Hungary, July 2004, 1163-1168. 
  • R.K. Price and D.P. Solomatine. Innovative approaches to flood forecasting using data driven and hybrid modeling. Proc. 6th Intern. Conf. on Hydroinformatics. Singapore, World Scientific, 2004.
  • B. Bhattacharya, R.K. Price, D.P. Solomatine. A data mining approach to modelling sediment transport. Proc. 6th Intern. Conf. on Hydroinformatics, Singapore, World Scientific, 2004.
  • D.P. Solomatine, M.B. Siek. Flexible and optimal M5 model trees with applications to flow predictions. Proc. 6th Intern. Conf. on Hydroinformatics, Singapore, World Scientific, 2004. 
  • B. Bhattacharya and D.P. Solomatine. Neural Networks and M5 Model Trees in Modelling Water Level-Discharge Relationship for an Indian River. Proc. 11th European Symposium on Artificial Neural Networks, Bruges, Belgium, April, 2003.
  • D.P. Solomatine. Data-driven modelling for flood-related problems. Proceedings of the NCR days 2003 (November), Roermond, Netherlands.
  • B. Bhattacharya and D.P. Solomatine. An algorithm for clustering and classification of series data with constraint of contiguity, Proc. 3rd International Conference on Hybrid Intelligent Systems (HIS'03), Melbourne, December 2003.
  • D.P. Solomatine. Mixtures of simple models vs ANNs in hydrological modeling. Proc. 3rd International Conference on Hybrid Intelligent Systems (HIS'03), Melbourne, December 2003.
  • S. Velickov, R.K. Price, D.P. Solomatine. Prediction of Nonlinear Dynamical Systems Based on Time Series Analysis: Issues of Entropy, Complexity and Predictability. Proceedings of the XXX IAHR Congress, Thessaloniki, Greece, August, 2003.
  • B. Bhattacharya, D.L. Shrestha, D.P. Solomatine. Neural Networks in Reconstructing Missing Wave Data in Sedimentation Modelling, Proceedings of the XXX IAHR Congress, Thessaloniki, Greece, August, 2003. 
  • B. Bhattacharya, D.P. Solomatine. Application of artificial neural networks and M5 model trees to modelling stage-discharge relationship, in: B.S. Wu, Z.Y. Wang, G.Q. Wang, G.H. Huang, H.W. Fang, and J.C. Huang, eds, Proc. of the 2nd International Symposium on Flood Defence, Beijing, China, Science Press New York Ltd., New York, 2003, pp.1029-1036.
  • M. Noguchi, D.P. Solomatine, W. Nishida. Calibration of Water Quality Model by Global Optimization Techniques. Proc. 5th Intern. Conf. on Hydroinformatics. Cardiff, UK, July 2002, pp. 464-469.
  • B. Bhattacharya, A.H. Lobbrecht, D.P. Solomatine. Control of water levels of regional water systems using reinforcement learning Proc. 5th Intern. Conf. on Hydroinformatics. Cardiff, UK, July 2002, pp. 952-957. 
  • D.P. Solomatine. Data-driven modelling: paradigm, methods, experiences. Proc. 5th Intern. Conf. on Hydroinformatics. Cardiff, UK, July 2002, pp.757-763.
  • Y. Dibike, A.H. Lobbrecht, D.P. Solomatine. Neural network and fuzzy logic technologies for control of the water system of Overwaard in The Netherlands. Proc. 5th Intern. Conf. on Hydroinformatics. Cardiff, UK, July 2002, pp.715-721.
  • D.P. Solomatine. Computational intelligence techniques in modeling water systems: some applications. Proc. World Congress on Computational Intelligence, USA, May 2002. 
  • D.P. Solomatine. Some applications of data-driven modelling and soft computing in control of water resources. International Conference on Computational Intelligence for Modelling Control and Automation (CIMCA'2001), 9-11 July 2001, USA. 
  • D.P. Solomatine, S. Velickov, J.C. Wust. Predicting water levels and currents in the North Sea using chaos theory and neural networks. Proc. XXXIX IAHR Congress, Beijing, September 2001.
  • S. Maskey, A. Jonoski, and D.P Solomatine. Use of Global Optimisation Technique in Groundwater Pumping Strategy for Plume Removal. In Groundwater Updates, Proc. of International Symposium 2000 on Groundwater, IAHR, Sato, K. and Iwasa, Y. (Eds.), May 2000, Saitama, Japan. (received "Groundwater Science and Engineering Award".)
  • R.K. Price, D.P. Solomatine, S. Velickov. Internet-based computing and knowledge management for engineering services. Proc. 4th Intern. Conf. on Hydroinformatics. Cedar-Rapids, USA, July 2000.
  • A.J Abebe., V. Guinot, D.P. Solomatine. Fuzzy alpha-cut vs. Monte Carlo techniques in assessing uncertainty in model parameters. Proc. 4th International Conference on Hydroinformatics. Cedar-Rapids, USA, July 2000.
  • B. Bhattacharia, D.P. Solomatine. Application of artificial neural network in stage-discharge relationship. Proc. 4th International Conference on Hydroinformatics. Cedar-Rapids, USA, July 2000. 
  • S. Velickov, D.P. Solomatine, X. Yu, R.K. Price. Application of Data Mining Techniques for Remote Sensing Image Analysis. Proc. 4th International Conference on Hydroinformatics. Cedar-Rapids, USA, July 2000. 
  • D.P. Solomatine, C. Rojas, S. Velickov, H. Wust. Chaos theory in predicting surge water levels in the North Sea. Proc. 4th International Conference on Hydroinformatics. Cedar-Rapids, USA, July 2000. 
  • B. Bazartseren, D.P. Solomatine, A.W. Minns, M.B. Abbott. Improving the quality of judgement in environmental impact assessment by using an analytic hierarchy process. Proc. XXVIII IAHR Congress, 22 27 August 1999, Graz, Austria. Technical University Graz, 1999.
  • D.P. Solomatine. Genetic and other global optimization algorithms - comparison and use in model calibration. Proc. 3rd Intern Conf. Hydroinformatics, Copenhagen, 1998, 1021-1028. 
  • S. Velickov, R.K. Price, D.P. Solomatine. Programming Internet for Hydroinformatics - an example of client/server modelling. Proc. 3rd Intern Conf. Hydroinformatics, Copenhagen, 1998, 965-972. 
  • R.K.Price, J. Samedov, D.P. Solomatine. Network modelling using artificial neural networks. Proc. 3rd Intern Conf. Hydroinformatics, Copenhagen, 1998, 813-818.
  • A.J Abebe., D.P. Solomatine. Application of global optimization to the design of pipe networks. Proc. 3rd Intern Conf. Hydroinformatics, Copenhagen, 1998, 989-996. 
  • D.P. Solomatine. Architectures of hydroinformatics systems: pressures from optimization and automatic calibration problems. Proc. 2nd Intern. Conf. on Hydroinformatics, Zurich, September 1996, 455 460.
  • C. Maksimovic, A. Verwey, D.P. Solomatine. Hydroinformatics in urban water infrastructure systems. Proc. 2nd Intern. Conf. on Hydroinformatics, Zurich, September 1996, 849  858.
  • D.P. Solomatine, L.A. Torres. Neural network approximation of a hydrodynamic model in optimizing reservoir operation. Proc. 2nd Intern. Conf. on Hydroinformatics, Zurich, September 1996, 201 206.
  • D.P. Solomatine. The use of global random search methods for models calibration. Proc. XXIVth IAHR Congress, September, 1995, London, vol.1, 224-229.
  • D.P. Solomatine, T.S. Tan. Optimal management of drainage facilities using object-oriented supervisory system. Proc. XXIVth IAHR Congress, September, 1995, London, vol.4, 423-424.
  • G. Vdovin., S. Middelhoek, M. Bartek, P.M. Sarro, D.P. Solomatine. Technology, characterization and applications of adaptive mirrors fabricated with IC-compatible micromachining. Proc. SPIE's Int. Symposium on Optical Science, Engineering and Instrumentation, Conference 'Adaptive Optical Systems and Applications', vol. 2534/13, San-Diego, USA, July 10-14, 1995.
  • D.P. Solomatine. Object orientation in hydroinformatics. Proc. 1st International Conference on Hydroinformatics, September 19-23, 1994, Delft, The Netherlands. Vol.1, 261-266. A.A.Balkema Publishers, Rotterdam:, 1994.
  • D.P. Solomatine, A.Vinovarov. Computer-Aided Stratification of Industrial Objects: Use of Binary Relations with Indifference Thresholds. Proc. of The 10th International Conference on Multiple Criteria Decision Making, Taiwan, Taipei, July 19 - 24, 1992.
  • D.P. Solomatine. Multi-Criteria Comparisons in the Presence of Additional Parameters and Indifference Threshold. Abstracts of Second International Conference on Industrial and Applied Mathematics, USA, Washington, July 8-12, 1991. ICIAM, Washington, 1991.
  • D.P. Solomatine. Problem structurization tools for pre-MCDM stage. Improving decision making in organizations. Proceedings of the 8th International Conference on Multi-Criteria Decision Making, U.K., Manchester, August 21-26, 1988.
  • D.P. Solomatine. Using structural modelling techniques in technological quality analysis. “Raising the Technological Level of Electronics Products”, Proc. Inter-Regional Symposium, Orel, 1988 (in Russian).
  • V. Borkovoi., A Vinovarov, D.P. Solomatine. Multicriterial analysis of technological quality. Issues and methods of decision making in management systems. Proc. of the 3rd All-Union Conference. Moscow - Zvenigorod, 1988 (in Russian).  
  • D.P. Solomatine. Interactive software for structural problem analysis. Proc. International Workshop 'Methodology and software for interactive decision support', Bulgaria, Albena, Oct.18 - 24, 1987. - Austria, Laxenburg: IIASA, 1987.
  • I.A. Ganin, D.P. Solomatine. Interactive modelling of problem situations structure in oranizational management. Proc. of the 10th All-Union Congress on Management and Control, vol. 2. Kazakhstan, Alma-Ata, September 1986 (in Russian).
  • D.P. Solomatine. Analysis of inter-organizational relations: using structural modelling. Methodology of Systems Studies, Proc. of the All-Union Symposium. Moscow - Lvov, 1985 (in Russian), pp. 198-199.
  • I.A. Ganin, D.P. Solomatine. A method of transitive binary relation reconstruction. Proc. All-Union Conference on Non-numerical Statistics, Expert assessments and Related Issues. Estonia, Tallinn, 1984 (in Russian).
  • D.P. Solomatine. Towards the multidisciplinary analysis of a complex object structure. - In: Methodology of systems studies, Proc. 1st All-Union School of Young Scientists, Moscow -Novogorsk, 1981 (in Russian).
  •  

Other research work