Using Fuzzy Clustering Analysis to Classify the Provinces of Iraq Based on Infrastructure Deprivation Levels
Saad Sabir Mohammed *
Statistics Department, College of Administration and Economics, Wasit University, Iraq.
Ola Hadi Sadeq
Statistics Department, College of Administration and Economics, Wasit University, Iraq.
Ahmed Razzaq Abed
Statistics Department, College of Administration and Economics, Wasit University, Iraq.
*Author to whom correspondence should be addressed.
Abstract
Aims: The research aims to use fuzzy clustering analysis to classify the provinces of Iraq based on their levels of infrastructure deprivation, by dependent on several indicators.
Study Design: Depending on the infrastructure indicators such as drinking water, sanitation, the time required to reach the source, waste collection, electricity stability and power supply, households' evaluation of infrastructure services, and the level of triple deprivation. For 18 governorates of Iraq.
Methodology: Central Agency for Statistics and Information Technology, basic tables, inventory and numbering results, environmental survey for the year 2010.
Results: Including the number of clusters that can be from the silhouette (Fc(U) equals 0.0390 corresponding to cluster four with reduction (Dc(U) equals 0.9036 corresponding to cluster four. Therefore we choose the number of clusters (4) clusters.
Conclusion: The fuzzy cluster analysis using the NCSS system (12) with the number of clusters (4) clusters showed that the most deprived governorates are Ninawa - Kirkuk - Anbar - Babylon - Wasit - Salah al-Din and the least deprived governorates are Dohuk - Erbil And Sulaymaniyah.
Keywords: Fuzzy concept, fuzzy c-means (FCM), fuzzy cluster structure viability test