TY - JOUR
T1 - Nonlinear system identification model of the spread of TB disease using the genetic algorithm and multilayer perceptron
AU - Damayanti, A.
AU - Subiyanto, P.
AU - Pratiwi, A. B.
N1 - Publisher Copyright:
© 2019 IOP Publishing Ltd. All rights reserved.
PY - 2019/9/9
Y1 - 2019/9/9
N2 - System identification is the process of building a mathematical model of a dynamic system based on the observed input-output data. Artificial neural networks have been shown to complete the identification of nonlinear systems with various learning algorithms. Identification of nonlinear dynamic systems in the model of TB disease spread is needed to predict the spread of TB disease. The model for the spread of TB disease has three compartments and six parameters. The process of identifying models for the spread of TB disease by estimating parameters using the genetic algorithm and validation of the model using multilayer perceptron. The choice of multilayer perceptron architecture determines the minimum error in the nonlinear system identification process for the model of TB disease spread. From the results of the trial, it was shown that the multilayer perceptron and genetic algorithm were able to identify the spread model of TB disease with MMRE of 0.00347
AB - System identification is the process of building a mathematical model of a dynamic system based on the observed input-output data. Artificial neural networks have been shown to complete the identification of nonlinear systems with various learning algorithms. Identification of nonlinear dynamic systems in the model of TB disease spread is needed to predict the spread of TB disease. The model for the spread of TB disease has three compartments and six parameters. The process of identifying models for the spread of TB disease by estimating parameters using the genetic algorithm and validation of the model using multilayer perceptron. The choice of multilayer perceptron architecture determines the minimum error in the nonlinear system identification process for the model of TB disease spread. From the results of the trial, it was shown that the multilayer perceptron and genetic algorithm were able to identify the spread model of TB disease with MMRE of 0.00347
UR - http://www.scopus.com/inward/record.url?scp=85072659338&partnerID=8YFLogxK
U2 - 10.1088/1742-6596/1306/1/012019
DO - 10.1088/1742-6596/1306/1/012019
M3 - Conference article
AN - SCOPUS:85072659338
SN - 1742-6588
VL - 1306
JO - Journal of Physics: Conference Series
JF - Journal of Physics: Conference Series
IS - 1
M1 - 012019
T2 - 2nd International Conference on Mathematics: Education, Theory, and Application, ICMETA 2018
Y2 - 30 October 2018 through 31 October 2018
ER -
