K-means Nearest Point Search Algorithm and Heuristic Search for Transportation

dc.contributor.author	Hlaing, Wai Mar
dc.contributor.author	Sein, Myint Myint
dc.date.accessioned	2020-12-17T17:45:44Z
dc.date.available	2020-12-17T17:45:44Z
dc.date.issued	2018-12-13
dc.identifier.isbn	978-1-538 6-6309-7
dc.identifier.issn	2378-8143
dc.identifier.uri	http://onlineresource.ucsy.edu.mm/handle/123456789/2539
dc.description.abstract	This paper aims to support the most suitable route for passengers of the taxi system using the proposed heuristic search method. Furthermore, k-Means Nearest Point Search (kMNPS) algorithm is proposed to produce the nearest road point for start and end addresses. Yangon downtown in Myanmar is selected as a case study for the transportation system. The proposed heuristic method and kMNPS algorithm reduce the distance calculations and achieve the very low time complexity for the real time transportation applications. Moreover, the proposed system can produce not only the optimal route on the map but also the popular spots near the optimal route.	en_US
dc.language.iso	en	en_US
dc.publisher	2018 IEEE 7th Global Conference on Consumer Electronics (GCCE)	en_US
dc.subject	Nearest Neighbor	en_US
dc.subject	K-means Clustering	en_US
dc.subject	Heuristic Search	en_US
dc.subject	Qgis	en_US
dc.subject	Weka	en_US
dc.title	K-means Nearest Point Search Algorithm and Heuristic Search for Transportation	en_US
dc.type	Article	en_US