Health is always considered as one of the most important issues related to human being. Due to this importance, governments should primarily provide the best healthcare services to their citizens. Some indicators can show the quality of healthcare services in the country. However, one country can have a higher value of one indicator and can have a lower value of another. Thus, countries can be categorized in terms of quality of healthcare services. Clustering is a useful tool for comparing countries and defining the similar countries in terms of healthcare services. In this study, 28 European Union (EU) countries were evaluated on 14 health factors and the number of clusters was determined by the generally accepted rule of thumb. To cluster countries, k-means clustering method is run in WEKA software for two cluster numbers and four different initial solution approaches. The resulting clusters were evaluated according to the Spearman rank correlation coefficient using the order of the GDP per capita values of the countries in each cluster. It seems using four clusters with Canopy initial solution approach is the most appropriate way of clustering.
Classification is defined as the problem of assignment of objects to the predefined classes. In general view, classification problems divided into two groups: classification and sorting problems. Sorting problems define the case of existence of ordered classes for objects, while classes are not ordered in classification problems. Besides these two groups of classification problems, Inverse Multiple Criteria Sorting Problem (IMSCP) is also introduced into the literature in recent years. IMSCP deals with finding the possible actions that can change the assignment of objects to classes in order to obtain the desired classification of objects. The main aim in this study is to propose an extension of IMSCP with fuzzy parameters with a proper solution approach. A case study of building energy labelling improvement in an existing building site in Ankara is solved by using parametric fuzzy solution approach of Carlsson and Korhonen. Obtained results of the application presents the possible actions to improve the energy labels of the buildings within the site. Also, solution results show that the proposed model in this study can be used to improve current Building Energy Performance model in Turkey to a new one with efficiency improvement suggestions.
Despite having child brings great responsibility, people want to have a child instinctively. In the context of childcare, parental responsibility requires that children should be born in good conditions and grow healthy and happily. Parents' first responsibility is to ensure that children born in a healthy way. Nowadays, pregnant women visit doctor regularly and monitor the infant development. There are too many doctors and hospitals working in obstetrics area. The increasing number of alternatives and selection criteria makes it difficult to find a compromise solution in terms of conflicting selection criteria. Therefore, using analytical methods becomes necessary while making the decision of hospital choice for pregnancy follow-up. The main aim of this study is to develop a decision tool for determining the best hospital for pregnancy process. Because of the existence of linguistic evaluations in the decision process, Fuzzy Analytic Hierarchy Process is used in this study for determining the best alternative. An application of a real world problem is presented to demonstrate the applicability of the proposed methodology. Within the presented application weight of hospital selection criteria and priority values of five predetermined alternative hospitals in Ankara are calculated are determined. The obtained results of the study shows that staff quality and technical conditions are the most important criteria for hospital selection.
Having a baby brings new changes and challenges in parents' life. There is a list of things which are required in order to provide a comfortable life for the baby. Since most of the people have limited economic resources, determination of the things to be bought becomes an important decision for parents. Moreover, the number of alternatives for the items in shopping list (bed, clothes, feeding equipment, stroller, etc.) is very much. Therefore, making a choice among alternative items is necessary. For each item, different alternatives have several advantages over another in views of different aspects. Consideration of several aspects of items would lead to good decisions, and parents must evaluate things in this way. It is aimed in this research to develop an analytic decision-making approach for stroller selection decision of parents. Hesitant fuzzy linguistic terms set (HFLTS) approach was presented in order to model the uncertain situations that the decision makers feel hesitant over various values of a linguistic variable. By using this pattern, elicitation of linguistic information is improved and thoughts of decision makers are represented better in decision models. Under the consideration of hesitant feelings of parents, HFLTS based group decision making approach is utilized to determine the optimum stroller. Apracticeof the presented model is presented to indicate its applicability and the presented decision approach seems useful for stroller selection.
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