| contributor author | McGovern, Amy | |
| contributor author | Elmore, Kimberly L. | |
| contributor author | Gagne, David John | |
| contributor author | Haupt, Sue Ellen | |
| contributor author | Karstens, Christopher D. | |
| contributor author | Lagerquist, Ryan | |
| contributor author | Smith, Travis | |
| contributor author | Williams, John K. | |
| date accessioned | 2017-06-09T16:46:35Z | |
| date available | 2017-06-09T16:46:35Z | |
| date issued | 2017 | |
| identifier issn | 0003-0007 | |
| identifier other | ams-73870.pdf | |
| identifier uri | http://onlinelibrary.yabesh.ir/handle/yetl/4216031 | |
| description abstract | is paper demonstrates that modern AI techniques can aid forecasters on a wide variety of high-impact weather phenomena. | |
| publisher | American Meteorological Society | |
| title | Using Artificial Intelligence to Improve Real-Time Decision Making for High-Impact Weather | |
| type | Journal Paper | |
| journal volume | 098 | |
| journal issue | 010 | |
| journal title | Bulletin of the American Meteorological Society | |
| identifier doi | 10.1175/BAMS-D-16-0123.1 | |
| journal fristpage | 2073 | |
| journal lastpage | 2090 | |
| tree | Bulletin of the American Meteorological Society:;2017:;volume( 098 ):;issue: 010 | |
| contenttype | Fulltext | |
