Quadratic tuned kernel parameter in non-linear support vector machine (SVM) for agarwood oil compounds quality classification

QR Code

Quadratic tuned kernel parameter in non-linear support vector machine (SVM) for agarwood oil compounds quality classification

This paper presents the analysis of agarwood oil compounds quality classification by tuning quadratic kernel parameter in Support Vector Machine (SVM). The experimental work involved of agarwood oil samples from low and high qualities. The input is abundances (%) of the agarwood oil compounds and th...

Full description

Bibliographic Details
Main Authors:	Muhamad Addin Akmal, Mohd Raif, Nurlaila, Ismail, Nor Azah, Mohd Ali, Mohd Hezri Fazalul, Rahiman, Saiful Nizam, Tajuddin, Mohd Nasir, Taib
Format:	Article
Language:	English
Published:	Institute of Advanced Engineering and Science 2019
Subjects:	Q Science (General) QD Chemistry T Technology (General) TP Chemical technology
Online Access:	http://umpir.ump.edu.my/id/eprint/33514/ http://umpir.ump.edu.my/id/eprint/33514/1/Quadratic%20tuned%20kernel%20parameter%20in%20non-linear%20support%20vector%20machine%20%28svm%29.pdf

Similar Items

Application of ANN in Agarwood Oil Grade Classification
by: Saiful Nizam, Tajuddin, et al.
Published: (2014)

Differentiating Agarwood Oil Quality Using Artificial Neural Network
by: Saiful Nizam, Tajuddin, et al.
Published: (2013)

A Review Study of Agarwood Oil and Its Quality Analysis
by: Nurlaila, Ismail, et al.
Published: (2014)

Classification of the Quality of Agarwood Oils from Malaysia using Z-Score Technique
by: Nurlaila, Ismail, et al.
Published: (2013)

Major Volatile Chemical Compounds of Agarwood Oils From Malaysia Based On Z-Score Technique
by: Nurlaila, Ismail, et al.
Published: (2015)

Direct Thermal Desorption (DTD) Extraction for Different Qualities of Agarwood Incense Analysis
by: Nurlaila, Ismail, et al.
Published: (2016)

Analysis Of High Quality Agarwood Oil Chemical Compounds By Means Of Spme/Gc-Ms And Z-Score Technique
by: Saiful Nizam, Tajuddin, et al.
Published: (2013)

Identification of Significant Compounds of Agarwood Incense Smoke Different Qualities using Z-Score
by: Nurlaila, Ismail, et al.
Published: (2015)

Analysis of Aroma Profile of Agarwood Incense Smoke by SPME and GCFID Combined with GC-MS
by: Nurlaila, Ismail, et al.
Published: (2015)

Analysis of agarwood smoke chemical compounds using solvent trap, GC-FID and GC-M
by: Nurlaila, Ismail, et al.
Published: (2017)

SVM modelling of agarwood oil quality grading using radial basis function (RBF) and sequential minimal optimization (SMO) learning algorithms
by: Muhammad Haziq Haikal, Hisham, et al.
Published: (2020)

Analysis of Chemical Compounds of Agarwood Oil based on Headspace-Solid Phase Microextraction combined with Gas Chromatography Mass-Spectrometry
by: Nurlaila, Ismail, et al.
Published: (2013)

Observation on SPME different headspace fiber coupled with GC-MS in extracting high quality agarwood chipwood
by: Nurlaila, Ismail, et al.
Published: (2016)

Analysis on agarwood vapour using headspace volatile DVB-CAR-PDMS SPME with different sampling time
by: Nurlaila, Ismail, et al.
Published: (2017)

Statistical Analysis of Agarwood Oil Compounds In Discriminating the Quality of Agarwood Oil
by: N. S. A., Zubir, et al.
Published: (2017)

Characterization of agarwood incense using gas chromatography – mass spectrometry (GC-MS) coupled with solid phase micro extraction (SPME) and gas chromatography - flame ionization detector (GC-FID) / Nurlaila Ismail … [et al.]
by: Ismail, Nurlaila, et al.
Published: (2015)

Development of web application for agarwood oil quality discriminator in virtualization platform
by: Mohamad Aqib Haqmi, Abas, et al.
Published: (2017)

Evaluation of energy consumption in small-scale agarwood distillation pot based on averaged control signal simulation
by: Nurul Nadia, Mohammad, et al.
Published: (2017)

Agarwood Oil Quality Classifier Using Machine Learning
by: M. A., Abas, et al.
Published: (2017)

The capabilities of Multiclass Support Vector Machine (MSVM) training algorithms in grading agarwood essential oil
by: Anis Hazirah ‘Izzati H., Al-Hadi, et al.
Published: (2024)

Determination of substantial chemical compounds of agarwood oil for quality grading
by: Mohamad Hushnie, Haron, et al.
Published: (2020)

Determination of agarwood oil’s significant chemical compounds using principal component analysis
by: Mohamad Hushnie, Haron, et al.
Published: (2020)

Analysis of algorithms variation in multilayer perceptron neural network for agarwood oil qualities classification
by: Nurul Shakila, Ahmad Zubir, et al.
Published: (2017)

Grading of agarwood oil quality based on its chemical compounds using self organizing map (SOM)
by: Mohamad Hushnie, Haron, et al.
Published: (2020)

Investigation of Common Compounds in High Grade and Low Grade Aquilaria Malaccensis using Correlation Analysis
by: Nurlaila, Ismail, et al.
Published: (2012)

Pattern classifier of chemical compounds in different qualities of agarwood oil parameter using scale conjugate gradient algorithm in MLP
by: Nurul Shakila, Ahmad Zubir, et al.
Published: (2017)

Evaluate the performance of SVM kernel functions for multiclass cancer classification
by: Mohd Hatta, Noramalina, et al.
Published: (2020)

Pengkelasan dokumen web menggunakan teknik vector machine (SVM)
by: Othman, Mohd. Shahizan, et al.
Published: (2005)

Improving machine vision crack die detection with multi-kernel learning SVM
by: Abdullah, Mohd Khairi John
Published: (2024)

Agarwood essential oil revolution
by: Saiful Nizam, Tajuddin
Published: (2014)

EEG analysis on actual and imaginary left and right hand lifting using Support Vector Machine (SVM) / Nabilah Hamzah .. [et al.]
by: Hamzah, Nabilah, et al.
Published: (2017)

Improved support vector machine using multiple SVM-RFE for cancer classification
by: Mohd Hasri, Nurul Nadzirah, et al.
Published: (2017)

King of Scents - Agarwood
by: Saiful Nizam, Tajuddin, et al.
Published: (2019)

Belajar Least Squares Support Vector Machines (LS-SVM) dalam masa seminggu
by: Mohd Herwan, Sulaiman, et al.
Published: (2017)

Automatic Arabic Recognition System based on Support Vector Machines (SVM)
by: Astuti, Winda, et al.
Published: (2011)

Agarwood oil quality identification using artificial neural network modelling for five grades
by: Siti Mariatul Hazwa, Mohd Huzir, et al.
Published: (2024)

A study on ann performance towards three significant compounds of high quality agarwood oil
by: Noratikah Zawani, Mahabob, et al.
Published: (2022)

Analysis of gc-fid and gc-ms microwave-assisted hydrodistillation extraction (mahd) of agarwood chips
by: Norfatirah, Muhamad Sarih, et al.
Published: (2021)

Pathway-based analysis with support vector machine (SVM-LASSO) for gene selection and classification
by: Nurul Athirah, Nasrudin, et al.
Published: (2017)

Pathway-based analysis with Support Vector Machine (SVM-LASSO) for gene selection and classification
by: Nasrudin, Nurul Athirah, et al.
Published: (2017)