The aim of this study is to classify the countries according to their tourism indicators via different cluster analysis methods and compare the findings. Using classical cluster analysis and fuzzy clustering together will be more appropriate to determine the World tourism structure. In this way the findings can be interpreted more detailed and comparatively. Data obtained from website of Worldbank (3 basic international tourism statistics of 159 countries for the year 2010) and findings are gained using NCSS (statistical software) 2007. According to the findings of fuzzy clustering method, Turkey belogs to a cluster which contains ABD, United Kingdom, China, Austria, France, Germany, Italy, Malaysia, Spain, Hong Kong, Russian Federation, and Ukraine. According to the findings of classical clustering method (k means), Turkey is in the same cluster with same countries except Hong Kong. Also the findings of two techniques are similar about Turkey. Such a result can be expected correspondingly grading the countries about international their tourism data in 2011. Different clustering methods findings are steady about Euroasian countries too. Except Russian Federation and Ukraine all of the other Euroasian countries are located together in same cluster depending upon two different clustering methods. In conclusion two different clustering methods provide consistent (similar) results about the classification of countries according their internatianol tourism statistics.
Classification of excessive domestic water consumption using Fuzzy Clustering Method