Safest Route Detection via Danger Index Calculation and K-Means Clustering
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Puthige, Isha | - |
dc.contributor.author | Bansal, Kartikay | - |
dc.contributor.author | Bindra, Chahat | - |
dc.contributor.author | Kapur, Mahekk | - |
dc.contributor.author | Singh, Dilbag | - |
dc.contributor.author | Mishra, Vipul Kumar | - |
dc.contributor.author | Aggarwal, Apeksha | - |
dc.contributor.author | Lee, Jinhee | - |
dc.contributor.author | Kang, Byeong-Gwon | - |
dc.contributor.author | Nam, Yunyoung | - |
dc.contributor.author | Mostafa, Reham R. | - |
dc.date.accessioned | 2021-09-10T06:27:03Z | - |
dc.date.available | 2021-09-10T06:27:03Z | - |
dc.date.issued | 2021 | - |
dc.identifier.issn | 1546-2218 | - |
dc.identifier.issn | 1546-2226 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/sch/handle/2021.sw.sch/19079 | - |
dc.description.abstract | The study aims to formulate a solution for identifying the safest route between any two inputted Geographical locations. Using the New York City dataset, which provides us with location tagged crime statistics; we are implementing different clustering algorithms and analysed the results comparatively to discover the best-suited one. The results unveil the fact that the K-Means algorithm best suits for our needs and delivered the best results. Moreover, a comparative analysis has been performed among various clustering techniques to obtain best results. we compared all the achieved results and using the conclusions we have developed a user-friendly application to provide safe route to users. The successful implementation would hopefully aid us to curb the ever-increasing crime rates; as it aims to provide the user with a beforehand knowledge of the route they are about to take. A warning that the path is marked high on danger index would convey the basic hint for the user to decide which path to prefer. Thus, addressing a social problem which needs to be eradicated from our modern era. | - |
dc.format.extent | 17 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | Tech Science Press | - |
dc.title | Safest Route Detection via Danger Index Calculation and K-Means Clustering | - |
dc.type | Article | - |
dc.publisher.location | 미국 | - |
dc.identifier.doi | 10.32604/cmc.2021.018128 | - |
dc.identifier.scopusid | 2-s2.0-85110518266 | - |
dc.identifier.wosid | 000677680600039 | - |
dc.identifier.bibliographicCitation | Computers, Materials and Continua, v.69, no.2, pp 2761 - 2777 | - |
dc.citation.title | Computers, Materials and Continua | - |
dc.citation.volume | 69 | - |
dc.citation.number | 2 | - |
dc.citation.startPage | 2761 | - |
dc.citation.endPage | 2777 | - |
dc.type.docType | Article | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Materials Science | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Information Systems | - |
dc.relation.journalWebOfScienceCategory | Materials Science, Multidisciplinary | - |
dc.subject.keywordAuthor | Agglomerative | - |
dc.subject.keywordAuthor | clustering | - |
dc.subject.keywordAuthor | crime rate | - |
dc.subject.keywordAuthor | danger index | - |
dc.subject.keywordAuthor | DBSCAN | - |
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