Identification of agarwood oil qualities using radial basis function (RBF) neural network / N. S. A. Zubir ...[et al.]

Agarwood is known as a valuable non-timber
product found in the dark fragrant resin in the stem, branch
and roots of certain species of Aquilaria. Agarwood oil is one of
the popular essential oil that has been used not only in Asian
but in the world. The price of the agarwood oil is referring
based on the quality of agarwood oil. The agarwood oil have
distinct pattern which can be discriminating the qualities of
agarwood oil by classification technique such as radial basis
function. The Radial Basis Function networks (RBFNs) are
commonly used for complex pattern classification. This study
examines the performance of radial basis function of
identifying the quality of agarwood oil either high or low
quality. The dataset consists of the abundances of significant
compounds (%) and qualities of the agarwood oil. The result
reveals that the classification using RBF technique, performs
slightly have a better performance of MSE values depends on
the 100 maximum numbers of neurons and 3 number of
spread. The hypothesis from this study is the larger number of
spread the smoother the function approximation. Besides that,
the small number of spread the large number of neurons
required to fit a smooth function.