Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/71862
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dc.contributor.authorVarin Chouvatuten_US
dc.contributor.authorEkkarat Boonchiengen_US
dc.contributor.authorWaraporn Boonchiengen_US
dc.date.accessioned2021-01-27T04:16:51Z-
dc.date.available2021-01-27T04:16:51Z-
dc.date.issued2021-01-01en_US
dc.identifier.issn20794029en_US
dc.identifier.issn16079264en_US
dc.identifier.other2-s2.0-85099364967en_US
dc.identifier.other10.3966/160792642020112106011en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85099364967&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/71862-
dc.description.abstract© 2020 Taiwan Academic Network Management Committee. All rights reserved. The aim of this research is to help support Provincial Public Health Offices (PPHOs) by clustering geographical coordinates in terms of latitudes and longitudes and comparing each cluster’s density in order to prevent mosquito-born diseases. In this research we propose using the hierarchically spatial clustering approach with two layers of clustering. We cannot use pre-existing clustering algorithms because they do not fit our purpose due to the naturally breeding area of common house mosquitoes. Thus, a modified method with an additional strict constraint of k-means and k-nearest neighbors were applied to meet this goal. Additional constraint to k-means clustering in the first layer will cause some of the coordinates to un-cluster. Finally, all coordinates must be clustered again to a second layer. However, the constraint of mosquito’s breeding area must be retained thus some falsely alarmed coordinates must be filtered out.en_US
dc.subjectComputer Scienceen_US
dc.titleClustering of domestic locations in layers for the purpose of breakout prevention of diseasesen_US
dc.typeJournalen_US
article.title.sourcetitleJournal of Internet Technologyen_US
article.volume21en_US
article.stream.affiliationsChiang Mai Universityen_US
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