− We discuss the concept of robustness with respect to parsing a context-free language. Our approach is based on the notions of fuzzy language, (generalized) fuzzy context-free grammar and parser / recognizer for fuzzy languages. As concrete examples we consider a robust version of Cocke−Younger−Kasami’s algorithm and a robust kind of recursive descent recognizer.

Fuzzy set theory has serious difficulties in producing valid answers in decision-making by fuzzifying judgments. No theorems are available about its workability when it is applied indiscriminately as a number crunching approach to numerical measurements that represent judgments. When judgments are allowed to vary in choice over the values of a fundamental scale, as in the Analytic Hierarchy Pro...

Multidimensional databases have become very popular for decision making frameworks. In this context, huge amounts of data are stored in data warehouses and decision makers try and navigate through this data using OLAP tools in order to visualize and analyze it. Although navigating through the data is one of the key issues, many issues are still open, and users are still not provided with intell...

Simulations and bisimulations between two fuzzy automata over a complete residuated lattice were defined by Ćirić et al. (2012) [7], [8] as relations the sets of states automata. However, they act crisp relationship In particular, if there exists (forward) bisimulation automata, then languages recognized them are crisply equal. Approximate simulations introduced Stanimirović (2022) [36] aim at ...

Institute of Mathematics of the Academy of Sciences of the Czech Republic provides access to digitized documents strictly for personal use. Each copy of any part of this document must contain these Terms of use. This paper has been digitized, optimized for electronic delivery and stamped with digital signature within the project DML-CZ: The Czech Digital Mathematics Library 1 We show how some c...

The objective in this paper is to present a framework for a system that describes objects in a qualitative fashion. A subset of spatial prepositions is chosen and an appropriate quantification is applied to each of them that capture their inherent qualitative properties. The quantifications use such object attributes as area, centers, and elongation properties. The familiar zeroth, first, and s...

The training time of ANN depends on size of ANN (i.e. number of hidden layers and number of neurons in each layer), size of training data, their normalization range and type of mapping of training patterns (like X–Y, X–DY, DX–Y and DX–DY), error functions and learning algorithms. The efforts have been done in past to reduce training time of ANN by selection of an optimal network and modificatio...

In this paper, we propose a fuzzy case-based reasoning system, using a case-based reasoning (CBR) system that learns from experience to solve problems. Different from a traditional case-based reasoning system that uses crisp cases, our system works with fuzzy ones. Specifically, we change a crisp case into a fuzzy one by fuzzifying each crisp case element (feature), according to the maximum deg...

This paper provides an innovative segmentation approach stemming from the combination of cluster analyses and fuzzy learning techniques. Our research provides a real case solution in the Spanish energy market to respond to the increasing number of requests from industry managers to be able to interpret ambiguous market information as realistically as possible. The learning stage is based on the...