This chapter discusses several issues related to the design of linguistic models with high interpretability using fuzzy genetics-based machine learning (GBML) algorithms. We assume that a set of linguistic terms has been given for each variable. Thus our modelling task is to find a small number of fuzzy rules from possible combinations of the given linguistic terms. First we formulate a threeob...

This paper argues that fuzzy representations are appropriate in applications where there are major sources of imprecision and/or uncertainty. Case studies of fuzzy approaches to specific problems of medical diagnosis and classification are described in support of this argument. The case studies are in the areas of categorical consistency, diagnostic monitoring and scoring. The solutions use a v...

Several useful models have been developed by the software engineering community to elucidate the periodic growth of life cycle and calculate the effort of cost estimation in a precise manner. One of the commonly used machine learning techniques is the analogy method that cannot handle the categorical variables efficiently. In general, project attributes of cost estimation are often measured in ...

The important field of research on ship operation is related to the high efficiency of transportation, the convenience of maneuvering ships, and the safety of navigation. This paper proposes an ontology-based fuzzy support agent for ship steering control and desires to testify the validity of the proposal by applying the fuzzy control model to the steering control system based on linguistic ins...

This paper proposes a fuzzy beam search rule induction algorithm for the classification task. The use of fuzzy logic and fuzzy sets not only provides us with a powerful, flexible approach to cope with uncertainty, but also allows us to express the discovered rules in a representation more intuitive and comprehensible for the user, by using linguistic terms (such as low, medium, high) rather tha...

We consider linguistic data(base) summaries in the sense of Yager [Information Sciences 28 (1982) 69–86], exemplified by ‘‘most employees are young and well paid’’ (with some degree of truth added), for a personnel database, as an intuitive, human consistent and natural language based knowledge discovery tool. We present first an extension of the classic Yager s approach to involve more sophist...

Fuzzy linguistic cognitive maps are considered. These maps are also applied to simulation of the well-known prisoner’s dilemma. This dilemma has provoked various challenges to game theory and decision making. By virtue of our approach we can use fuzzy rules and reasoning when computer models are constructed. We also aim to show that our approach seems usable in general when complicated phenomen...

In recent two decades, countries focused on minimum extraction of fossil fuels and utilized the renewable energies based on countries' policies and the environmental considerations. Thus, choosing the best renewable energy alternative is a significant role to investment on them. Among the classical decision approaches that have used in the literature, the hesitant fuzzy sets (HFSs) theory is ap...

We propose a new, human consistent method for the evaluation of similarity of time series that uses a fuzzy quantifier base aggregation of trends (segments), within the authors’ (cf. Kacprzyk, Wilbik, Zadrożny [1, 2, 3, 4, 5, 6] or Kacprzyk, Wilbik [7, 8, 9]) approach to the linguistic summarization of trends based on Zadeh’s protoforms and fuzzy logic with linguistic quantifiers. The results o...

We present an entirely new approach for the representation of intensifying and weakening linguistic hedges in fuzzy set theory, which is primarily based on a crisp ordering relation associated with the term that is modified, as well as on a fuzzy quantifier. With this technique we can generate membership functions for both atomic and modified linguistic terms. We prove that our model respects s...