Implementasi Jaringan Syaraf Tiruan Recurrent Menggunakan Gradient Descent Adaptive Learning Rate and Momentum Untuk Pendugaan Curah Hujan
The artificial neural network (ANN) technology in rainfall prediction can be done using the learning approach. The ANN prediction accuracy is measured by the determination coefficient (R2) and root mean square error (RMSE). This research implements Elman’s Recurrent ANN which is heuristically optimi...
Main Authors: | Afan Galih Salman, Yen Lina Prasetio |
---|---|
Format: | Article |
Language: | English |
Published: |
Bina Nusantara University
2011-06-01
|
Series: | ComTech |
Subjects: | |
Online Access: | https://journal.binus.ac.id/index.php/comtech/article/view/2707 |
Similar Items
-
Implementasi Jaringan Syaraf Tiruan Recurrent Dengan Metode Pembelajaran Gradient Descent Adaptive Learning Rate Untuk Pendugaan Curah Hujan Berdasarkan Peubah Enso
by: Afan Galih Salman, et al.
Published: (2010-12-01) -
Pemodelan debit banjir berdasarkan data curah hujan menggunakan jaringan syaraf tiruan
by: , PRIBADI, Feddy Setio, et al.
Published: (2007) -
Belief-Rule-Base Inference Method Based on Gradient Descent With Momentum
by: Yu Guan, et al.
Published: (2021-01-01) -
IMPLEMENTASI ALGORITMA PELATIHAN LEVENBERG MARQUARDT DAN BAYES REGULARISASI PADA JARINGAN SYARAF TIRUAN UNTUK PREDIKSI CURAH HUJAN
(Studi Kasus : Stasiun pengamatan curah hujan Pangsuma Putussibau, Kalimantan Barat)
by: , Yasinta Lisa, et al.
Published: (2012) -
Discrete Missing Data Imputation Using Multilayer Perceptron and Momentum Gradient Descent
by: Hu Pan, et al.
Published: (2022-07-01)