| contributor author | Manish Kumar Goyal | |
| contributor author | C. S. P. Ojha | |
| date accessioned | 2017-05-08T21:49:56Z | |
| date available | 2017-05-08T21:49:56Z | |
| date copyright | April 2014 | |
| date issued | 2014 | |
| identifier other | %28asce%29he%2E1943-5584%2E0000828.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl/handle/yetl/63702 | |
| description abstract | Climate change scenarios generated by general circulation models (GCMs) have too coarse a spatial resolution to be useful in planning disaster risk reduction and climate change adaptation strategies at regional to river/lake basin scales. This paper investigates the performances of existing state-of-the-art rule induction and tree algorithms, namely, single conjunctive rule learner, decision table, M5P model tree, decision stump, and REPTree. Downscaling models are developed to obtain projections of mean monthly maximum and minimum temperatures ( | |
| publisher | American Society of Civil Engineers | |
| title | Evaluation of Rule and Decision Tree Induction Algorithms for Generating Climate Change Scenarios for Temperature and Pan Evaporation on a Lake Basin | |
| type | Journal Paper | |
| journal volume | 19 | |
| journal issue | 4 | |
| journal title | Journal of Hydrologic Engineering | |
| identifier doi | 10.1061/(ASCE)HE.1943-5584.0000795 | |
| tree | Journal of Hydrologic Engineering:;2014:;Volume ( 019 ):;issue: 004 | |
| contenttype | Fulltext | |
