Type-2 Fuzzy Rule-Based Model of Urban Metro Positioning Service
In the last few years there has been a growing interest in route building oriented mobile applications with the following features of navigation and sending timely notifications about arrival. Despite the large body of existing knowledge on navigational services, there has been an important issue relative to positioning accuracy. The paper discusses a possible solution to comparison problem, which is linked to the determination of the closeness to destination metro station through finding a difference between user’s current coordinates and fixed-point coordinates. With this end in view, fuzzy logic approach is used to develop Routes Recommender System (RRS) that utilizes linguistic variables to express the vague and uncertain term ‘closeness to…’. The paper provides detailed explanation of each variable considered in the fuzzy inference system (FIS), set of fuzzy rules in line with graphical representation of system’s output. Based on Mamdani model, we propose a set of test cases to check maintainability of the model and provide a description about received results. At a later time, an Android-based mobile application aimed at public transport route building will be developed whose notification system will be based on our model`s implementation presented. It should be emphasized that the paper examines potentials of the modeling approach based on interval type-2 fuzzy sets (IT2FS) that attract much attention these days in various research studies and conventional Mamdani fuzzy inference system (MFIS) as applied to real and rather topical problem. The significance of developing such models may be of a high demand for appropriate representation of factors that are inherently vague and uncertain. Hence, this study may also contribute to future research on similar topics.