Pheromone-based Kohonen Self-Organizing Map (PKSOM) in clustering of tropical wood species: Performance and scalability

Azlin Ahmad, Rubiyah Yusof, Yasue Mitsukura

研究成果: Conference contribution

2 被引用数 (Scopus)

抄録

Clustering is proposed to cluster the high dimensional data, into clusters of data that exhibit some similarities. Due to this ability, it has been chosen to solve many problems in various areas, including tropical wood species classification. It has ease the recognition process which has been done manually before. Pheromone-based Kohonen Self-Organizing Map (PKSOM) is proposed a clustering tool to cluster the wood datasets; the filtered and raw datasets. This paper discusses the performance and scalability of modified Kohonen Self-Organizing Map (KSOM), named Pheromone-based KSOM (PKSOM). The PKSOM algorithm is trained and tested using two types of wood datasets; the raw wood dataset and filtered dataset using Genetic Algorithm (GA). The results are then being compared with two conventional clustering methods; KSOM and standard K-Mean. As a conclusion, PKSOM has produced 97.5% of accuracy for the raw wood dataset and 97.55% for the filtered wood dataset, slightly higher compared to the other two methods.

本文言語English
ホスト出版物のタイトル2015 10th Asian Control Conference
ホスト出版物のサブタイトルEmerging Control Techniques for a Sustainable World, ASCC 2015
編集者Hazlina Selamat, Hafiz Rashidi Haruna Ramli, Ahmad Athif Mohd Faudzi, Ribhan Zafira Abdul Rahman, Asnor Juraiza Ishak, Azura Che Soh, Siti Anom Ahmad
出版社Institute of Electrical and Electronics Engineers Inc.
ISBN(電子版)9781479978625
DOI
出版ステータスPublished - 2015 9月 8
イベント10th Asian Control Conference, ASCC 2015 - Kota Kinabalu, Malaysia
継続期間: 2015 5月 312015 6月 3

出版物シリーズ

名前2015 10th Asian Control Conference: Emerging Control Techniques for a Sustainable World, ASCC 2015

Other

Other10th Asian Control Conference, ASCC 2015
国/地域Malaysia
CityKota Kinabalu
Period15/5/3115/6/3

ASJC Scopus subject areas

  • 制御およびシステム工学

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