| contributor author | Gokmen Tayfur | |
| contributor author | Vijay P. Singh | |
| date accessioned | 2017-05-08T20:45:21Z | |
| date available | 2017-05-08T20:45:21Z | |
| date copyright | December 2006 | |
| date issued | 2006 | |
| identifier other | %28asce%290733-9429%282006%29132%3A12%281321%29.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl/handle/yetl/26041 | |
| description abstract | This study presents the development of artificial neural network (ANN) and fuzzy logic (FL) models for predicting event-based rainfall runoff and tests these models against the kinematic wave approximation (KWA). A three-layer feed-forward ANN was developed using the sigmoid function and the backpropagation algorithm. The FL model was developed employing the triangular fuzzy membership functions for the input and output variables. The fuzzy rules were inferred from the measured data. The measured event based rainfall-runoff peak discharge data from laboratory flume and experimental plots were satisfactorily predicted by the ANN, FL, and KWA models. Similarly, all the three models satisfactorily simulated event-based rainfall-runoff hydrographs from experimental plots with comparable error measures. ANN and FL models also satisfactorily simulated a measured hydrograph from a small watershed | |
| publisher | American Society of Civil Engineers | |
| title | ANN and Fuzzy Logic Models for Simulating Event-Based Rainfall-Runoff | |
| type | Journal Paper | |
| journal volume | 132 | |
| journal issue | 12 | |
| journal title | Journal of Hydraulic Engineering | |
| identifier doi | 10.1061/(ASCE)0733-9429(2006)132:12(1321) | |
| tree | Journal of Hydraulic Engineering:;2006:;Volume ( 132 ):;issue: 012 | |
| contenttype | Fulltext | |
