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This study investigates the performance of the Multilayer Perceptron (MLP) classifier in discriminating the qualities of agarwood oil significant compounds by different qualities based on three training algorithms namely Scaled Conjugate Gradient (SCG), Levernbergh-Marquardt (LM) and Resilient Backpropagation (RP) Neural Network by using Matlab version 2013a. The dataset used in this study were obtained...
This paper presents the modelling of agarwood oil (AO) significant compounds by different qualities using Scaled Conjugate Gradient (SCG) algorithm. This technique involved of data collection from Gas Chromatography-Mass Spectrometry (GC-MS) for compound extraction. The development of Multilayer perceptron (MLP) is used to discriminate the qualities of AO chemical compounds to the high and low quality...
In recent years, the demand for agarwood oil has increased tremendously. Agarwood oil is being used widely in fragrance, incense and religious ceremony. The quality of agarwood oil will determine the price of the oil. However, there are some limitations on using standard approach to classify its quality as they are time consuming, expensive and the results is questionable. This paper presents on the...
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