Development and Validation of GANN Model for Evapotranspiration Estimation
| contributor author | M. Kumar | |
| contributor author | N. S. Raghuwanshi | |
| contributor author | R. Singh | |
| date accessioned | 2017-05-08T21:24:29Z | |
| date available | 2017-05-08T21:24:29Z | |
| date copyright | February 2009 | |
| date issued | 2009 | |
| identifier other | %28asce%291084-0699%282009%2914%3A2%28131%29.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl/handle/yetl/50291 | |
| description abstract | The present study was carried out to develop generalized artificial neural network (GANN) based reference crop evapotranspiration models corresponding to FAO-56 PM, FAO-24 Radiation, Turc, and FAO-24 Blaney–Criddle methods. The generalized ANN models were developed using the data from four California Irrigation Management Information System (CIMIS) stations, namely, Davis, Castroville, Mulberry, and West Side Field Station. The average weighted standard error of estimate (WSEE) for the developed models, namely, GANN (4-5-1), GANN (3-4-1), GANN (5-6-1), and GANN (6-7-1) corresponding to the FAO-24 Blaney–Criddle, FAO-24 Radiation, Turc, and FAO-56PM was 0.72, 0.85, 0.63, and | |
| publisher | American Society of Civil Engineers | |
| title | Development and Validation of GANN Model for Evapotranspiration Estimation | |
| type | Journal Paper | |
| journal volume | 14 | |
| journal issue | 2 | |
| journal title | Journal of Hydrologic Engineering | |
| identifier doi | 10.1061/(ASCE)1084-0699(2009)14:2(131) | |
| tree | Journal of Hydrologic Engineering:;2009:;Volume ( 014 ):;issue: 002 | |
| contenttype | Fulltext |
