engleski

Positioning of Public Service Systems Using Uncertain Data Clustering

Positioning of public service system is crucial and very challenging task. Proper positioning ensures that the public service system would complete its tasks to the end users. This paper is focused on finding the best location for public service system, to improve its efficiency when using uncertain data clustering. By choosing the best location for the service system the respond time can be minimised, and the given tasks could be performed in a reasonable time. Improved bisector pruning method was proposed for clustering previous data of public service system to find the best location for its application. Presented method can be used for different Public Service Systems, like traffic services, positioning of ambulance vehicles and other mobile objects. Cluster centres are used as best locations for public service systems because, cluster centres minimized total expected distance from tasks that have been set to the service system. On this way, public service system will be improved and can fulfil more tasks during the shortest period of time

clustering ; data mining ; expected distance ; service systems ; uncertain data

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