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.
|Journal||MATEC Web of Conferences|
|Publication status||Published - 01 Jan 2014|
|Event||4th International Conference on Production, Energy and Reliability, ICPER 2014 - Kuala Lumpur, Malaysia|
Duration: 03 Jun 2014 → 05 Jun 2014
All Science Journal Classification (ASJC) codes
- Materials Science(all)