Abstract
Increasing our understanding of typhoon movements remains a priority in the western North Pacific. In this study, the trajectories of typhoons that affected Taiwan between 1986 and 2010 are used for clustering, where each trajectory consists of 6-hourly latitude-longitude positions over two days. We compare the performance of four statistical clustering methods, namely, k-means clustering, fuzzy c-means (FCM) clustering, hierarchical clustering, and normalized cut techniques. The results show that the FCM technique provides sufficient cluster efficiency with a relatively high degree of goodness of fit. FCM identifies six clusters according to the minimum coefficients of variation (CV). The hotspots of the typhoon centers in each cluster are determined by kernel density estimation (KDE). Moreover, the typhoon track belongs to six clusters with different membership degrees in FCM. The typhoon track density map is estimated by combining the KDE hotspot maps associated with the FCM weights. The information could be used in planning for disaster management.
| Original language | English |
|---|---|
| Pages (from-to) | 9451-9457 |
| Number of pages | 7 |
| Journal | Expert Systems With Applications |
| Volume | 39 |
| Issue number | 10 |
| DOIs | |
| Publication status | Published - 2012 Aug 1 |
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All Science Journal Classification (ASJC) codes
- Artificial Intelligence
- Computer Science Applications
- Engineering(all)
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Integration of fuzzy cluster analysis and kernel density estimation for tracking typhoon trajectories in the Taiwan region. / Chu, Hone-Jay; Liau, Churn Jung; Lin, Chao-Hung; Su, Bo Song.
In: Expert Systems With Applications, Vol. 39, No. 10, 01.08.2012, p. 9451-9457.Research output: Contribution to journal › Article
TY - JOUR
T1 - Integration of fuzzy cluster analysis and kernel density estimation for tracking typhoon trajectories in the Taiwan region
AU - Chu, Hone-Jay
AU - Liau, Churn Jung
AU - Lin, Chao-Hung
AU - Su, Bo Song
PY - 2012/8/1
Y1 - 2012/8/1
N2 - Increasing our understanding of typhoon movements remains a priority in the western North Pacific. In this study, the trajectories of typhoons that affected Taiwan between 1986 and 2010 are used for clustering, where each trajectory consists of 6-hourly latitude-longitude positions over two days. We compare the performance of four statistical clustering methods, namely, k-means clustering, fuzzy c-means (FCM) clustering, hierarchical clustering, and normalized cut techniques. The results show that the FCM technique provides sufficient cluster efficiency with a relatively high degree of goodness of fit. FCM identifies six clusters according to the minimum coefficients of variation (CV). The hotspots of the typhoon centers in each cluster are determined by kernel density estimation (KDE). Moreover, the typhoon track belongs to six clusters with different membership degrees in FCM. The typhoon track density map is estimated by combining the KDE hotspot maps associated with the FCM weights. The information could be used in planning for disaster management.
AB - Increasing our understanding of typhoon movements remains a priority in the western North Pacific. In this study, the trajectories of typhoons that affected Taiwan between 1986 and 2010 are used for clustering, where each trajectory consists of 6-hourly latitude-longitude positions over two days. We compare the performance of four statistical clustering methods, namely, k-means clustering, fuzzy c-means (FCM) clustering, hierarchical clustering, and normalized cut techniques. The results show that the FCM technique provides sufficient cluster efficiency with a relatively high degree of goodness of fit. FCM identifies six clusters according to the minimum coefficients of variation (CV). The hotspots of the typhoon centers in each cluster are determined by kernel density estimation (KDE). Moreover, the typhoon track belongs to six clusters with different membership degrees in FCM. The typhoon track density map is estimated by combining the KDE hotspot maps associated with the FCM weights. The information could be used in planning for disaster management.
UR - http://www.scopus.com/inward/record.url?scp=84862784995&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84862784995&partnerID=8YFLogxK
U2 - 10.1016/j.eswa.2012.02.114
DO - 10.1016/j.eswa.2012.02.114
M3 - Article
AN - SCOPUS:84862784995
VL - 39
SP - 9451
EP - 9457
JO - Expert Systems with Applications
JF - Expert Systems with Applications
SN - 0957-4174
IS - 10
ER -