Aplikasi Metode Generalized Reduced Gradient dalam Pemodelan Curah Hujan-Limpasan Menggunakan Artificial Neural Network (ANN)

Abstract

The rainfall run off modelling is necessary until now days, for fulling data or make data longer. Artificial neural network can made the alternative rainfall run off modelling. The implementation Artificial neural networ for modelling on the water resources which is done by researcher to get an accurate result. Artificial neural networ is one of artificial intelligent that is imitation of representation from brain of human. This model is the black box modelling, so in the implementation were not need complecity of scient among the other aspect in the process of rainfall run off modelling. The case study applied to the river flow on the way Sekampung river in Lampung Province. The data used is rainfall data and stream flow data in the middle of the month on the water level station Pujorahayu, for 19 years from 1983 up to 2001. The rainfall data is input and stream flow is a variable output. Learning method that is used reduced gradient. From the result of this research got correlation coefficient 0,790 or 79 % the tallest. The conclution of this research is the generaly ANN can implementated in the rainfall run off modeling, although the result is not too accurate because of there is still deviation.

Keywords: rainfall-runoff, artificial neural network, black box, generalized reduced gradient

Permalink: http://ejournal.undip.ac.id/index.php/mkts/article/view/3907

[How to cite: Hadihardaja, I.K. dan Sutikno, S., 2005, Aplikasi Metode Generalized Reduced Gradient dalam Pemodelan Curah Hujan-Limpasan Menggunakan Artificial Neural Network (ANN), Jurnal Media Komunikasi Teknik Sipil, Volume 13, Nomor 2, pp. 37-49]