چکیده مقاله
River flow forecasting can reduce excessive water deficiencies flood damages and enhance proper management of agricultural water supplies however development of an appropriate river flow forcasting model is a complex process despite numrous applications of multilayer perceptron neural networks MLP in river flow forcasting there is not any application using the cerebellar model articulation controller CMAC thus in this research two algorithms namely MLP with error backpropagation and CMAC are developed and applied for forcasting monthly inflows to dez reservoir located in southwestern iran
کلیدواژهها
نویسندگان
a.m moradi
graduated student
a.b dariane
associate professor
m. teshnehlab
a.m moradi graduated studenta.b dariane associate professor
شیوه ارجاع
moradi, a.m and dariane, a.b and teshnehlab, m.,1391,Montly river flow forcasting using CMAC and MLP neural networks case study dez reservoir,9th International Congress on Civil Engineering,Isfahan
ارائهشده در
مجموعه مقالات نهمین کنگره بین الملی مهندسی عمران19 اردیبهشت 1391 · اصفهان