| Title: | Autocalibration experiments using machine learning and high performance computing |
| Authors: | Sloboda, M. and D.A. Swayne |
| Year: | 2013 |
| Journal: | Environmental Modelling & Software |
| Volume (Issue): | 40 |
| Pages: | 302-315 |
| Article ID: | |
| DOI: | 10.1016/j.envsoft.2012.10.007 |
| URL (non-DOI journals): | |
| Model: | SWAT |
| Broad Application Category: | hydrologic and pollutant |
| Primary Application Category: | computational efficiency |
| Secondary Application Category: | calibration, sensitivity, and/or uncertainty analysis |
| Watershed Description: | Raisin River in southern Ontario, Canada |
| Calibration Summary: | |
| Validation Summary: | |
| General Comments: | |
| Language: | English |
| Keywords: | Automatic calibration, Multiobjective calibration, High performance computing, Machine learning, SWAT, Probably, approximately correct learning |