The SCEAS System
Navigation Menu

Search the dblp DataBase

Title:
Author:

Dimitri P. Solomatine: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Michael Baskara L. A. Siek, Dimitri P. Solomatine
    Optimizing Mixtures of Local Experts in Tree-Like Regression Models. [Citation Graph (0, 0)][DBLP]
    Artificial Intelligence and Applications, 2005, pp:497-502 [Conf]
  2. Biswanath Bhattacharya, Dimitri P. Solomatine
    Neural Networks and M5 model trees in modeling water level-discharge relationship for an Indian river. [Citation Graph (0, 0)][DBLP]
    ESANN, 2003, pp:407-412 [Conf]
  3. Biswanath Bhattacharya, Dimitri P. Solomatine
    An Algorithm for Clustering and Classification of Series Data with Constraint of Contiguity. [Citation Graph (0, 0)][DBLP]
    HIS, 2003, pp:489-498 [Conf]
  4. Dimitri P. Solomatine
    Mixtures of Simple Models vs ANNs in Hydrological Modeling. [Citation Graph (0, 0)][DBLP]
    HIS, 2003, pp:77-85 [Conf]
  5. Biswanath Bhattacharya, Dimitri P. Solomatine
    Neural networks and M5 model trees in modelling water level-discharge relationship. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 2005, v:63, n:, pp:381-396 [Journal]
  6. Durga L. Shrestha, Dimitri P. Solomatine
    Experiments with AdaBoost.RT, an Improved Boosting Scheme for Regression. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2006, v:18, n:7, pp:1678-1710 [Journal]
  7. Biswanath Bhattacharya, Dimitri P. Solomatine
    Machine learning in soil classification. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 2006, v:19, n:2, pp:186-195 [Journal]
  8. Biswanath Bhattacharya, Dimitri P. Solomatine
    Machine learning in sedimentation modelling. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 2006, v:19, n:2, pp:208-214 [Journal]
  9. Vladimir Cherkassky, Vladimir M. Krasnopolsky, Dimitri P. Solomatine, Julio J. Valdés
    2006 Special issue: Earth Sciences and Environmental Applications of Computational IntelligenceIntroduction. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 2006, v:19, n:2, pp:111- [Journal]
  10. Vladimir Cherkassky, Vladimir M. Krasnopolsky, Dimitri P. Solomatine, John J. Valdés
    Computational intelligence in earth sciences and environmental applications: Issues and challenges. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 2006, v:19, n:2, pp:113-121 [Journal]
  11. Durga L. Shrestha, Dimitri P. Solomatine
    Machine learning approaches for estimation of prediction interval for the model output. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 2006, v:19, n:2, pp:225-235 [Journal]
  12. Dimitri P. Solomatine, M. B. Siek
    Modular learning models in forecasting natural phenomena. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 2006, v:19, n:2, pp:215-224 [Journal]
  13. Dimitri P. Solomatine
    Adaptive cluster covering and evolutionary approach: comparison, differences and similarities. [Citation Graph (0, 0)][DBLP]
    Congress on Evolutionary Computation, 2005, pp:1959-1966 [Conf]
  14. Gerald Corzo, Dimitri P. Solomatine
    Knowledge-based modularization and global optimization of artificial neural network models in hydrological forecasting. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 2007, v:20, n:4, pp:528-536 [Journal]
  15. Vladimir Cherkassky, William Hsieh, Vladimir M. Krasnopolsky, Dimitri P. Solomatine, Julio J. Valdés
    Computational intelligence in earth and environmental sciences. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 2007, v:20, n:4, pp:433- [Journal]

  16. ANNs and Other Machine Learning Techniques in Modelling Models' Uncertainty. [Citation Graph (, )][DBLP]


  17. Eager and Lazy Learning Methods in the Context of Hydrologic Forecasting. [Citation Graph (, )][DBLP]


  18. Improving Empirical Models with Machine Learning. [Citation Graph (, )][DBLP]


  19. Learning hydrologic flow separation algorithm and local ANN committee modeling. [Citation Graph (, )][DBLP]


  20. Comparing machine learning methods in estimation of model uncertainty. [Citation Graph (, )][DBLP]


  21. Multivariate chaotic models vs neural networks in predicting storm surge dynamics. [Citation Graph (, )][DBLP]


Search in 0.002secs, Finished in 0.003secs
NOTICE1
System may not be available sometimes or not working properly, since it is still in development with continuous upgrades
NOTICE2
The rankings that are presented on this page should NOT be considered as formal since the citation info is incomplete in DBLP
 
System created by asidirop@csd.auth.gr [http://users.auth.gr/~asidirop/] © 2002
for Data Engineering Laboratory, Department of Informatics, Aristotle University © 2002