DocumentCode :
1953357
Title :
Enhancing Clustering Technique to Plan Social Infrastructure Services
Author :
Salman, H.A. ; Ibrahim, L.F. ; Fayed, Z.
Author_Institution :
Dept. of Inf. Syst., King Abdulaziz Univ., Jeddah, Saudi Arabia
fYear :
2013
fDate :
29-31 Jan. 2013
Firstpage :
18
Lastpage :
23
Abstract :
This article deals with social infrastructure planning problems in urban city. Each facility must serve minimum pre-specified level of demand. The objective is to minimize the distance traveled by users to reach the facilities this means also to maximize the accessibility to facilities. A location model that captures the above features is formulated and different solution methods are tested. Clustering in spatial data mining is to group similar objects based on their connectivity, distance, or their relative density in space. In real word, there exist many physical obstacles such as rivers, lakes, highways and mountains, and their presence may affect the result of clustering significantly. In this paper, we study the problem of clustering in the presence of obstacles to solve location of public service facility problem. In this paper, CSPOD-DBSCAN algorithm (Clustering with short path Obstructed Distance - Density- Based Spatial Clustering of Applications with Noise) is developed in the spirit of DBSCAN clustering algorithms. This algorithm is Density-based clustering algorithm using Dijkstra algorithm to calculate obstructed short path distance. The application of this algorithm is illustrated through a case study involving the location of schools in the districts of Mecca in Saudi Arabia.
Keywords :
data mining; educational institutions; pattern clustering; town and country planning; CSPOD-DBSCAN algorithm; DBSCAN clustering algorithms; Dijkstra algorithm; Mecca districts; Saudi Arabia; clustering technique enhancement; clustering-with-short path obstructed distance algorithm; density-based clustering algorithm; density-based spatial clustering-of-applications-with-noise algorithm; facility accessibility maximization; object connectivity; object distance; object relative density; obstructed short path distance; physical obstacles; public service facility problem; school location; similar object grouping; social infrastructure service planning problems; spatial data mining; urban city; user distance traveled minimization; Clustering algorithms; Data mining; Educational institutions; Planning; Sociology; Spatial databases; Statistics; DBSCAN Clustering algorithm; infrastructure city planning; Spatial Clustering algorithm; Urban Planning; public service facility;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Systems Modelling & Simulation (ISMS), 2013 4th International Conference on
Conference_Location :
Bangkok
ISSN :
2166-0662
Print_ISBN :
978-1-4673-5653-4
Type :
conf
DOI :
10.1109/ISMS.2013.97
Filename :
6498228
Link To Document :
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