Please use this identifier to cite or link to this item:
http://dspace.uniten.edu.my/jspui/handle/123456789/6974
Title: | On-line condition monitoring system for high level trip water in steam Boiler's Drum | Authors: | Alnaimi, F.B.I. A Ali, M. Al-Kayiem, H.H. Mohamed Sahari, K.S.B. |
Issue Date: | 2014 | Abstract: | This paper presents a monitoring technique using Artificial Neural Networks (ANN) with four different training algorithms for high level water in steam boiler's drum. Four Back-Propagations neural networks multidimensional minimization algorithms have been utilized. Real time data were recorded from power plant located in Malaysia. The developed relevant variables were selected based on a combination of theory, experience and execution phases of the model. The Root Mean Square (RMS) Error has been used to compare the results of one and two hidden layer (1HL), (2HL) ANN structures. © 2014 Owned by the authors, published by EDP Sciences. | URI: | http://dspace.uniten.edu.my/jspui/handle/123456789/6974 |
Appears in Collections: | COE Scholarly Publication |
Show full item record
Google ScholarTM
Check
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.