Khursiah Zainal-Mokhtar

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This paper presents novel research on the development of a generic intelligent oil fraction sensor based on Electrical Capacitance Tomography (ECT) data. An artificial Neural Network (ANN) has been employed as the intelligent system to sense and estimate oil fractions from the cross-sections of two-component flows comprising oil and gas in a pipeline.(More)
The main goal of the presented work is to analyse the performance of the Multi-Layer Perceptron (MLP) neural network for flow regime classification based on sets of simulated Electrical Capacitance Tomography (ECT) data. Normalised ECT data have been used to separately train several MLPs employing various commonly used back-propagation learning algorithms,(More)
Artificial Neural Network (ANN) has been shown to be a robust tool for intelligent recognition. In every intelligent recognition task, the first dilemma would be the correct size of training data, since too few is definitely not sufficient while too many may lead to over training problem. This paper presents a study on the dimensionality of training data(More)
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