TY  - JOUR
KW  - Backpropagation; Carbon dioxide; Gas emissions; Linear programming; Liquefied natural gas; Neural networks; Regulatory compliance; Simulated annealing; Support vector machines
KW  -  Analytical Instrumentation; Back propagation neural networks; Continuous emission monitoring system; Industrial pollution; Least squares support vector regression; Nelder-mead simplex algorithms; Predictive algorithms; Predictive techniques
KW  -  Support vector regression
ID  - scholars3150
N2  - This paper aims to develop a CO2 emission model of an acid gas incinerator using Nelder-Mead least squares support vector regression (LS-SVR). The Malaysia Department of Environment is actively imposing the Clean Air Regulation to mandate heavy industries to comply with emission limits. One of the latest measures is to mandate the installation of analytical instrumentation known as a continuous emission monitoring system (CEMS) to report the emission level online to the Department of Environment office. As a hardware-based analyser, CEMS is expensive, maintenance intensive and often unreliable. Therefore, software predictive techniques are often preferred and considered a feasible alternative to replace the CEMS for regulatory compliance. The LS-SVR model is built based on the emissions from an acid gas incinerator that operates in a liquefied natural gas complex. Simulated annealing is first used to determine the initial hyper-parameters, which are further optimized based on the performance of the model using a Nelder-Mead simplex algorithm. The LS-SVR model is shown to outperform a benchmark model based on back-propagation neural networks in both training and testing data. © The Author(s) 2012.
IS  - 8
Y1  - 2012///
VL  - 34
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84869054610&doi=10.1177%2f0142331211425404&partnerID=40&md5=5977e623a0455e68cc578d3bfb69fa60
A1  - Pathmanathan, E.
A1  - Ibrahim, R.
A1  - Asirvadam, V.S.
JF  - Transactions of the Institute of Measurement and Control
AV  - none
TI  - Development of CO2 emission model of an acid gas incinerator using Nelder-Mead least squares support vector regression
SP  - 974
N1  - cited By 2
SN  - 01423312
PB  - SAGE Publications Ltd
EP  - 982
ER  -