A new approach of ranking of Gaussian fuzzy numbers and application in choice of mHealth app

In many real-world situations, data are imprecise or linguistic in nature. In such cases, fuzzy numbers are useful to represent this imprecision. Various types of fuzzy numbers have been proposed, among which Gaussian fuzzy numbers are particularly effective for handling vague data, because they provide a more flexible and realistic representation. In this study, a ranking method for the Gaussian fuzzy numbers is developed and illustrated with examples. In multi criteria decision making (MCDM) problems, the criteria associated with a set of alternatives often conflict. Moreover, the available data are not always certain. In such situations, the application of Gaussian fuzzy numbers is crucial for data representation. In addition, each criterion does not generally have equal importance to decision-makers. Therefore, the fuzzy analytic hierarchy process (FAHP) has been introduced. Using the proposed ranking method and FAHP, an application has been presented to select the best option from a set of mHealth applications.