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Spatial Clustering based Meteorological Fields Construction for Regional Vulnerability Assessment

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BibTeX

@article{IJASEIT5759,
   author = {Taemin Lee and Woosung Choi and Jongryuel Sohn and Kyongwhan Moon and Sanghoon Byeon and Wookyun Lee and Soonyoung Jung},
   title = {Spatial Clustering based Meteorological Fields Construction for Regional Vulnerability Assessment},
   journal = {International Journal on Advanced Science, Engineering and Information Technology},
   volume = {8},
   number = {4-2},
   year = {2018},
   pages = {1686--1691},
   keywords = {spatial clustering; vulnerability assessment; meteorological field; DBSCAN},
   abstract = {Chemical accidents have affected the social-environmental system. For the regional vulnerability assessment, which is the baseline work to assess the impact on the environment, a meteorological field is needed to determine how chemicals from multiple adjacent companies are propagated. In this study, we present the method of meteorological field based on the spatial cluster which is the main component of vulnerability assessment on regional chemical accident scenario. To integrate spatially dense chemical companies into a cluster, we adopt spatial clustering algorithms. Experiment result shows that DBSCAN-based approach reduces 80.5% total area of the meteorological field against brute-force algorithm, and shows good performance on the average of the overlap ratio, and utility ratio for clustering results.},
   issn = {2088-5334},
   publisher = {INSIGHT - Indonesian Society for Knowledge and Human Development},
   url = {http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=5759},
   doi = {10.18517/ijaseit.8.4-2.5759}
}

EndNote

%A Lee, Taemin
%A Choi, Woosung
%A Sohn, Jongryuel
%A Moon, Kyongwhan
%A Byeon, Sanghoon
%A Lee, Wookyun
%A Jung, Soonyoung
%D 2018
%T Spatial Clustering based Meteorological Fields Construction for Regional Vulnerability Assessment
%B 2018
%9 spatial clustering; vulnerability assessment; meteorological field; DBSCAN
%! Spatial Clustering based Meteorological Fields Construction for Regional Vulnerability Assessment
%K spatial clustering; vulnerability assessment; meteorological field; DBSCAN
%X Chemical accidents have affected the social-environmental system. For the regional vulnerability assessment, which is the baseline work to assess the impact on the environment, a meteorological field is needed to determine how chemicals from multiple adjacent companies are propagated. In this study, we present the method of meteorological field based on the spatial cluster which is the main component of vulnerability assessment on regional chemical accident scenario. To integrate spatially dense chemical companies into a cluster, we adopt spatial clustering algorithms. Experiment result shows that DBSCAN-based approach reduces 80.5% total area of the meteorological field against brute-force algorithm, and shows good performance on the average of the overlap ratio, and utility ratio for clustering results.
%U http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=5759
%R doi:10.18517/ijaseit.8.4-2.5759
%J International Journal on Advanced Science, Engineering and Information Technology
%V 8
%N 4-2
%@ 2088-5334

IEEE

Taemin Lee,Woosung Choi,Jongryuel Sohn,Kyongwhan Moon,Sanghoon Byeon,Wookyun Lee and Soonyoung Jung,"Spatial Clustering based Meteorological Fields Construction for Regional Vulnerability Assessment," International Journal on Advanced Science, Engineering and Information Technology, vol. 8, no. 4-2, pp. 1686-1691, 2018. [Online]. Available: http://dx.doi.org/10.18517/ijaseit.8.4-2.5759.

RefMan/ProCite (RIS)

TY  - JOUR
AU  - Lee, Taemin
AU  - Choi, Woosung
AU  - Sohn, Jongryuel
AU  - Moon, Kyongwhan
AU  - Byeon, Sanghoon
AU  - Lee, Wookyun
AU  - Jung, Soonyoung
PY  - 2018
TI  - Spatial Clustering based Meteorological Fields Construction for Regional Vulnerability Assessment
JF  - International Journal on Advanced Science, Engineering and Information Technology; Vol. 8 (2018) No. 4-2
Y2  - 2018
SP  - 1686
EP  - 1691
SN  - 2088-5334
PB  - INSIGHT - Indonesian Society for Knowledge and Human Development
KW  - spatial clustering; vulnerability assessment; meteorological field; DBSCAN
N2  - Chemical accidents have affected the social-environmental system. For the regional vulnerability assessment, which is the baseline work to assess the impact on the environment, a meteorological field is needed to determine how chemicals from multiple adjacent companies are propagated. In this study, we present the method of meteorological field based on the spatial cluster which is the main component of vulnerability assessment on regional chemical accident scenario. To integrate spatially dense chemical companies into a cluster, we adopt spatial clustering algorithms. Experiment result shows that DBSCAN-based approach reduces 80.5% total area of the meteorological field against brute-force algorithm, and shows good performance on the average of the overlap ratio, and utility ratio for clustering results.
UR  - http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=5759
DO  - 10.18517/ijaseit.8.4-2.5759

RefWorks

RT Journal Article
ID 5759
A1 Lee, Taemin
A1 Choi, Woosung
A1 Sohn, Jongryuel
A1 Moon, Kyongwhan
A1 Byeon, Sanghoon
A1 Lee, Wookyun
A1 Jung, Soonyoung
T1 Spatial Clustering based Meteorological Fields Construction for Regional Vulnerability Assessment
JF International Journal on Advanced Science, Engineering and Information Technology
VO 8
IS 4-2
YR 2018
SP 1686
OP 1691
SN 2088-5334
PB INSIGHT - Indonesian Society for Knowledge and Human Development
K1 spatial clustering; vulnerability assessment; meteorological field; DBSCAN
AB Chemical accidents have affected the social-environmental system. For the regional vulnerability assessment, which is the baseline work to assess the impact on the environment, a meteorological field is needed to determine how chemicals from multiple adjacent companies are propagated. In this study, we present the method of meteorological field based on the spatial cluster which is the main component of vulnerability assessment on regional chemical accident scenario. To integrate spatially dense chemical companies into a cluster, we adopt spatial clustering algorithms. Experiment result shows that DBSCAN-based approach reduces 80.5% total area of the meteorological field against brute-force algorithm, and shows good performance on the average of the overlap ratio, and utility ratio for clustering results.
LK http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=5759
DO  - 10.18517/ijaseit.8.4-2.5759