In the real world, many situations involve dealing with vague and imprecise information, and managing this uncertainty is a big challenge. Numerical-based modeling alone is often insufficient in such cases. As a result, many researchers have implemented fuzzy signatures as a means to overcome this problem. However, there are instances where parameters remain ambiguous, and determining the fuzzy membership degree and membership function as inputs and outputs of such a system is not possible. Therefore, integrating fuzzy signatures with linguistic descriptors provides a more realistic approach to handling uncertain knowledge about the problem. This paper aims to discuss the new fuzzy linguistic signature model, which offers a unique solution by enabling the incorporation of qualitative and quantitative information and explores its potential applications. A software entirely based on linguistic inputs and outputs has been implemented to demonstrate the concept.

Decision-making is a key process for human beings, and it is becoming more complicated in the case of uncertainty. Thus, it may be a more realistic approach to use linguistic values instead of numerical values. In the literature, there have been numerous applications for fuzzy signatures for modelling decision-making problems with uncertainty. However, there are application cases where the parameters are not measurable, and there is no way to assign precise membership values and functions to the variables. The main goal of this paper is to propose a way to make a decision about traffic related questions, using a new model for fuzzy linguistic signatures with linguistic aggregation operations in this case. Telemetric data collected by the Hungarian e-toll declaration provider are utilized for the purpose of the example. The results demonstrate the efficiency and time-saving advantages of employing fuzzy linguistic signatures over to numerical methods for decision-making.