Open AccessPemodelan Sistem dengan Metode Neural Network Back Propagation Modeling System Using Neural Network Backpropagation
Author(s) -
Dwi Sudarno Putra,
Toto Sugiarto,
Meri Azmi
Publication year - 2016
Publication title -
jurnal ilmiah poli rekayasa
Language(s) - English
Resource type - Journals
eISSN - 2685-3922
pISSN - 1858-3709
DOI - 10.30630/jipr.11.2.24
Subject(s) - backpropagation , artificial neural network , computer science , process (computing) , artificial intelligence , time delay neural network , noise (video) , stochastic neural network , machine learning , algorithm , image (mathematics) , operating system
A system can be modeled using mathematical formulation analysis method. Analysis of the system starts from the value of inputs, processes, noise, and output processes. then sought mathematical approach. This method is very complex, especially for some of the processes that have a higher order. In this article the author tries to discuss a method to perform modeling on a system by using Back Propagation Neural Network method.In the neural network method we require the initial data for network training process. Network training process is intended to gain weight. The weight is then identified with a model system. This paper has demonstrated that the modeling system can be done by the method of back propagation neural network