A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf
.
Capacitance–Based Tomography Flow Pattern Classification Using Intelligent Classifiers With Voting Technique
2011
Jurnal Teknologi
^m^'fq^k'bJ_^pba=qljldo^mev=cilt=m^qqbok= i^ppfcf'^qflk=rpfkd=fkqbiifdbkq='i^ppfcfbop=tfqe= slqfkd=qb'ekfnrb= grkfq^=jle^j^aJp^ibe NG I=olpifk=g^j^irafk O== C=e^cfw^e=q^if_ P = = Äëíê~ÅíK This paper presents a method for Electrical Capacitance Tomography (ECT) flow classification using voting technique, employing Multilayer Perceptrons (MLPs) as the intelligent pattern classifiers. MLP classifiers were trained with a set of simulated ECT data associated to various flow patterns and was tested
doi:10.11113/jt.v55.892
fatcat:q64sglhjsran3pgmv5uhkazso4