Pemodelan Generator Uap Berbasis Jaringan Saraf Tiruan dengan Algoritme Pelatihan BPGD-ALAM - Fadhlia Annisa; Agfianto Eko Putra (IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia., 2016)
Steam generator is unit plant which has nonlinear and complex system with multiple-input-multiple-output (MIMO) configuration which is hard to be modeled. Whereas, steam generator model is very useful to create simulation such as operator training simulator (OTS). The purpose of this research is to obtain model of steam generator which has 8 output parameters and 9 input parameters based neural network (NN) with BPGD-ALAM training algorithm. Data had been taken from steam generator of PT. Chevron Pacific Indonesia, Duri and it is divided into three types, i.e training data, validation data and testing data. Training data was used to obtain model for each ouput through training process. Verification model is also done for each epoch using validation data to monitor training process whether overfitting occurs or not. Eight NN model of each output which is obtained from training and verification, is tested using testing data for getting its performance. From the reseach results, architecture of neural network models are obtained with various configuration for each output with RMSE value under 9.71 %. It shows that model which has been obtained, close with steam generator real system.