Information granules have been considered as the fundamental constructs of Granular Computing. As a useful unsupervised learning technique, Fuzzy C-Means (FCM) is one most frequently used methods to construct information granules. The FCM-based granulation–degranulation mechanism plays pivotal role in In this paper, enhance quality degranulation (reconstruction) process, we augment by introduci...

In this research, we introduce a classification procedure based on rule induction and fuzzy reasoning. The classifier generalizes attribute information to handle uncertainty, which often occurs in real data. To induce rules, define the corresponding system. A transformation of derived rules into interval type-2 is provided as well. fuzzification applied optimized with respect footprint uncertai...

This paper extends some authors’ previous approaches to models and methods based on fuzzy sets and fuzzy logic, for the seismic fragility updating and seismic damage evaluation, in their contributions to the IFIP 8 Conference (Krakow – 1998), SMiRT 16 (Washington DC – 2001) and SMiRT 18 (Beijing – 2005) Conferences. A short survey of such earlier and more recent proposals for applying fuzzy con...

Methods for analyzing or learning from “fuzzy data” have attracted increasing attention in recent years. In many cases, however, existing methods (for precise, non-fuzzy data) are extended to the fuzzy case in an ad-hoc manner, and without carefully considering the interpretation of a fuzzy set when being used for modeling data. Distinguishing between an ontic and an epistemic interpretation of...

The paper presents a mathematical framework for approximate geometric reasoning with extended objects in the context of Geography, in which all entities and their relationships are described by human language. These entities could be labelled by commonly used names of landmarks, water areas, and so forth. Unlike single points that are given in Cartesian coordinates, these geographic entities ar...

Information from load profile is useful for electricity suppliers to plan their generation, improving their market strategies and load balancing. Consumers in the new liberalized market have the opportunity of choosing their electricity suppliers between several suppliers and the possibility to access to new products and services from them. Hence they need the knowledge of load profile to help ...

Algorithms for preprocessing databases with incomplete and imprecise data are seldom studied. For the most part, we lack numerical tools to quantify the mutual information between fuzzy random variables. Therefore, these algorithms (discretization, instance selection, feature selection, etc.) have to use crisp estimations of the interdependency between continuous variables, whose application to...

Fuzzy cellular automata (FCA) are continuous cellular automata where the local rule is defined as the “fuzzification” of the local rule of a corresponding Boolean cellular automaton in disjunctive normal form. In this paper we are interested in the relationship between Boolean and fuzzy models and we analytically show, for the first time, the existence of a strong connection between them by foc...

This paper offers a new technique for designing fuzzy controllers as analog hardware devices on bases of CMOS implementation of multi-valued logical functions. This approach is based on using a summing amplifier with saturation as a building block that can be considered as a multi-threshold logical element. The functional completeness in an arbitrary-valued logic of a summing amplifier with sat...