1285164
doi
10.5281/zenodo.1285164
oai:zenodo.org:1285164
Elkhawad Elfaki
Department of mechanical Engineering, Bisha University, Bisha, Saudi Arabia
Prediction of Electrical Output Power of Combined Cycle Power Plant Using Regression ANN Model
Ahmed Hassan Ahmed Hassan
Department of mechanical Engineering, Ondokuz Mayis University, Samsun, Turkey
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
Neural Networks
Regression
Combined Power Cycle
MATLAB Neural Networks Toolbox
<p>Recently, regression artificial neural networks are used to model various systems that have high dimensionality with nonlinear relations. The system under study must have enough dataset available to train the neural network. The aim of this work is to apply and experiment various options effects on feed-foreword artificial neural network (ANN) which used to obtain regression model that predicts electrical output power (EP) of combined cycle power plant based on 4 inputs. Dataset is obtained from an open online source. The work shows and explains the stochastic behavior of the regression neural, experiments the effect of number of neurons of the hidden layers. It shows also higher performance for larger training dataset size; at the other hand, it shows different effect of larger number of variables as input. In addition, two different training functions are applied and compared. Lastly, simple statistical study on the error between real values and estimated values using ANN is conducted, which shows the reliability of the model. This paper provides a quick reference to the effects of main parameters of regression neural networks. </p>
Zenodo
2018-06-05
info:eu-repo/semantics/article
1285163
1579541096.103221
4519007
md5:eecda85b9cf721e65448fdb06cabf96d
https://zenodo.org/records/1285164/files/CCPP using ANN .pdf
public
10.5281/zenodo.1285163
isVersionOf
doi
International Journal of Computer Science and Control Engineering
6
2
9-21
2018-06-05