Harun, Sobri and Nor, Nor Irwan Ahmat and Harun, Sobri and Kassim, Amir Hashim Mohd. (2007) Radial basis function modeling of hourly streamflow hydrograph. Journal Of Hydrologic Engineering, 12 (1). pp. 113-123. ISSN 1084-0699
Official URL: http://dx.doi.org/10.1061/(ASCE)1084-0699(2007)12:...
An artificial neural network is well known as a flexible mathematical tool that has the ability to generalize patterns in imprecise or noisy and ambiguous input and output data sets. The radial basis function (RBF) method is applied to model the relationship between rainfall and runoff for Sungai Bekok Catchment (Johor, Malaysia) and Sungai Ketil catchment (Kedah, Malaysia). The RBF is used to predict the streamflow hydrograph based on storm events. Evaluation on the performance of RBF is demonstrated based on errors (between predicted and actual) and comparison with the results of the Hydrologic Engineering Center hydrologic modeling system model. It is obvious that the RBF method offers an accurate modeling of streamflow hydrograph.
|Uncontrolled Keywords:||Rainfall, runoff, streamflow, hydrographs|
|Subjects:||T Technology > TA Engineering (General). Civil engineering (General)|
|Deposited By:||INVALID USER|
|Deposited On:||25 Nov 2009 02:14|
|Last Modified:||02 Jun 2010 01:55|
Repository Staff Only: item control page