Agarwood oil grade clustering of aquilaria malaccensis species using Extraction by GC-MS analysis: Efficient KNN algorithm based on patterns visualization of two-dimensional graph

Agarwood oil grade clustering of aquilaria malaccensis species using Extraction by GC-MS analysis: Efficient KNN algorithm based on patterns visualization of two-dimensional graph

Data visualization pattern is an essential task in data analysis. A two-dimensional graph (2D graph) is one of the graphical presentations for data visualization. Over the past decades, Agarwood Oil grade clustering is still at a disadvantage since there is no official standard grading system. Most...

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Bibliographic Details
Main Authors: Siti Mariatul Hazwa, Mohd Huzir, Anis Hazirah ‘Izzati H., Al-Hadi, Amir Hussairi, Zaidi, Nurlaila F., Ismail, Zakiah, Mohd Yusoff, Saiful Nizam, Tajuddin, Mohd Nasir, Taib
Format: Article
Language:English
English
Published: Malaysian Institute of Chemistry 2024
Subjects:
HD Industries. Land use. Labor
Q Science (General)
T Technology (General)
Online Access:http://umpir.ump.edu.my/id/eprint/43643/
http://umpir.ump.edu.my/id/eprint/43643/1/Agarwood%20oil%20grade%20clustering%20of%20aquilaria%20malaccensis%20species.pdf
http://umpir.ump.edu.my/id/eprint/43643/2/Agarwood%20oil%20grade%20clustering%20of%20aquilaria%20malaccensis%20species%20using%20extraction%20by%20GC-MS%20analysis_Efficient%20KNN%20algorithm%20based%20on%20patterns_abs.pdf

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