TY - GEN
T1 - Identifying the dominant species of tropical wood species using histogram intersection method
AU - Ahmad, Azlin
AU - Yusof, Rubiyah
AU - Mitsukura, Yasue
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015
Y1 - 2015
N2 - This research is addresses to determine the dominant species that located in the overlapped clusters produced by the Kohonen Self-organizing Map (KSOM). Before, KSOM algorithm able to cluster the tropical wood species data set effectively and accurately according to the wood features, which is wood pores sizes. Unfortunately, there are seven overlapped clusters in the clustering result and this is due to similarity features among the wood species. This problem has caused difficulty in determining the separation boundary amongst clusters, where the most dominant species for every overlapped cluster is difficult to identify. As for a solution, the Histogram Intersection (HI) method is proposed in this research to solve this problem. From the experiments, the HI has proved that it can determine the dominant species of the overlapped clusters effectively resulting in an improvement of 1.12% of the classification accuracy, compared with the clustering result without HI technique. It has shown the implementation of this method has successfully solved the problem occurred.
AB - This research is addresses to determine the dominant species that located in the overlapped clusters produced by the Kohonen Self-organizing Map (KSOM). Before, KSOM algorithm able to cluster the tropical wood species data set effectively and accurately according to the wood features, which is wood pores sizes. Unfortunately, there are seven overlapped clusters in the clustering result and this is due to similarity features among the wood species. This problem has caused difficulty in determining the separation boundary amongst clusters, where the most dominant species for every overlapped cluster is difficult to identify. As for a solution, the Histogram Intersection (HI) method is proposed in this research to solve this problem. From the experiments, the HI has proved that it can determine the dominant species of the overlapped clusters effectively resulting in an improvement of 1.12% of the classification accuracy, compared with the clustering result without HI technique. It has shown the implementation of this method has successfully solved the problem occurred.
KW - Clustering
KW - Pheromone-Based KSOM (PKSOM)
KW - Tropical Wood Species
KW - pheromone
UR - http://www.scopus.com/inward/record.url?scp=84973098140&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84973098140&partnerID=8YFLogxK
U2 - 10.1109/IECON.2015.7392572
DO - 10.1109/IECON.2015.7392572
M3 - Conference contribution
AN - SCOPUS:84973098140
T3 - IECON 2015 - 41st Annual Conference of the IEEE Industrial Electronics Society
SP - 3075
EP - 3080
BT - IECON 2015 - 41st Annual Conference of the IEEE Industrial Electronics Society
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 41st Annual Conference of the IEEE Industrial Electronics Society, IECON 2015
Y2 - 9 November 2015 through 12 November 2015
ER -