Abstract
Intuitionistic fuzzy sets (IFSs), including member and nonmember functions, have many applications in managing uncertain information. The similarity measures of IFSs proposed to represent the similarity between different types of sensitive fuzzy information. However, some existing similarity measures do not meet the axioms of similarity. Moreover, in some cases, they could not be applied appropriately. In this study, we proposed some novel similarity measures of IFSs constructed by combining the exponential function of membership functions and the negative function of non-membership functions. In this paper, we also proposed a new entropy measure as a stepping-stone to calculate the weights of the criteria in the proposed multi-criteria decision-making (MCDM) model. The similarity measures used to rank alternatives in the model. Finally, we used this MCDM model to evaluate the quality of software projects.
Highlights
In 1986, Atanassov introduced intuitionistic fuzzy sets (IFSs) (Atanassov, 1986), which are a generalization of a fuzzy set (Zadeh, 1965)
We proposed a new entropy measure as a stepping stone to calculate the weights of the criteria in the proposed multi-criteria decision making (MCDM) model
The evaluation of software quality based on ISO standards (IOS, 2017) associated with the difficulty is that most of the standards are qualitative
Summary
In 1986, Atanassov introduced intuitionistic fuzzy sets (IFSs) (Atanassov, 1986), which are a generalization of a fuzzy set (Zadeh, 1965). An IFS considers the information involving membership functions and non-membership functions From their inception to the present day, IFSs have been proven to be a highly effective tool for processing uncertainties in real-world problems, including pattern recognition and decision-making. In 2016, Ye introduced similarity measures of IFSs based on the cosine function for decision-making in mechanical design schemes (Ye, 2016). We applied new measures on IFSs to the problem of pattern recognition and decision-making software quality assessment. Definition 2. (Li and Cheng, 2002) A mapping S: IFS(X ) IFS(X ) [0,1] is the similarity measure of the intuitionistic fuzzy sets if it satisfies the following conditions:
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