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Let L be a fuzzy propositional logic based on triangular norm min(x,y) (Zadeh's logic). A fact in L is an expression of the form r ≤ ϕ ≤ s where ϕ ∈ L and 0 ≤ r ≤ s ≤ 1. In fuzzy interpretation I of L every fact is true or false, and I(r ≤ ϕ ≤ s) = 1 if and only if the two-side inequality r ≤ I(ϕ) ≤ s is satisfied. Thus, the set FL of all facts defines a crisp logic with fuzzy interpretations. Logical...
The purpose of this paper is to present briefly the conceptual framework of fairness in the consensus reaching process with novel elements of grasping imprecision in intentions, preferences and adjustments of individuals. All solutions are based on the idea of “soft” degree of consensus under fuzzy preference relations and a fuzzy majority given as a fuzzy linguistic quantifier. Here, we propose a...
Precision Agriculture is becoming an unavoidable approach for farmers aiming to improve their businesses. Technologies that were once used only by urban companies are being used in agriculture in order to maximize their production, reducing the costs. In this sense, this work proposes to apply environmental sensing technologies to assist farmers to detect the probability of occurrence (or proliferation)...
In this paper, a new hybrid method for forming interval type 2 fuzzy inference systems (IT2 FIS) is shown. This methodology builds upon an existing type 1 fuzzy inference system (T1 FIS) or from the output centers from any clustering algorithm, calculating the footprint of uncertainty (FOU) based on the implementation of the principle of justifiable granularity, and finally a particle swarm optimization...
The game-theoretic rough set (GTRS) model provides a configuration mechanism for determination of thresholds in probabilistic rough sets. The GTRS utilizes different approaches in implementing games for analyzing various applications and problems. The probabilistic thresholds and the key game components such as players and strategies may be interpreted differently based on a particular formulation...
Defining a proper measure of proximity (or remoteness) between two groups of objects is of crucial importance in applied research. Much attention has been paid to consideration of continuous-valued attributes while nominal-valued attributes seems to be more difficult to handle. In this paper we defined non empty groups of objects, and each group is described as K-tuple sets of attributes values. Next,...
The concept of bipolar linguistic summaries of data, introduced by Dziedzic, Zadrożny and Kacprzyk [1], is further developed. These summaries are meant as an extension of the “classical” linguistic summarization [2], [3], a human-consistent data mining technique, making it possible to express more complex patterns present in data. The focus of the paper is to provide a deeper insight into the very...
This paper investigates rough clustering of objects from uncertain databases using possibility and rough set theories. Real databases can contain both certain and uncertain attribute values. To properly cluster such instances into different clusters, it is necessary to take into account such uncertainty. When clustering objects with uncertain values, we have to consider the similarities between each...
Principal curves, as a nonlinear generalization of principal components, are a common tool used in multivariate analysis for ends like dimensionality reduction and feature extraction. However, one of the difficulties that arise when utilizing this technique is that efficiency of existing principal curves algorithms is often low when dealing with large data set owing to high computational complexity...
Following the Computing With Words, in its wider sense, this paper examines the treatment of prepositions with fuzzy logic. In particular, the paper looks at the treatment of two prepositions, in and on, from both the theoretical perspective and that of a text sample analysis. We have shown that the fuzzy analysis of prepositional meaning is helpful for its formal and computational representation,...
Any conceptual computer or computing with words (CW) system is expected to represent its results with a reasonable output, such as a sentence in natural language. A CW system is required to translate the fuzzy values provided as its result into words. This paper explores different similarity measures as well as linguistic approximation methods for generating natural language sentences for CW systems...
The users see social networks as a platform for exchanging their opinions about posted items. Such behavior is easily observed in tagging systems. Tagging is a process of annotating, by a single user, any items available on the network - called resources - by individuals. Items labeled by users, and labels used by users can be exploited to construct signatures representing users' activities and interests...
Granular computing is a rapidly growing area of information processing aimed at the construction of intelligent systems. The paper suggests how to combine granular computing with regression analysis. Multidistances are applied for generating granular partitions of data sets. Several areas of potential applications of the granular regression are indicated.
We approach the problem of measuring consensus for a set of real inputs by aggregating the fuzzy implication degrees between each pair of inputs. We compare our operator with existing consensus measures in terms of their satisfaction of desirable properties. The appeal of such an approach lies in the interpretability and flexibility that results from component-wise construction which we modeled on...
Fuzzy cognitive maps (FCMs) are a very convenient and simple tool for modeling complex systems. They are popular due to their simplicity and user friendliness. However, according to [1], human experts are subjective and can handle only relatively simple networks therefore there is an urgent need to develop methods for automated generation of FCM models. The present research deals with the methodology...
Fuzzy ontologies provide an efficient tool to represent and utilize imprecise and vague data in decision making problems. In the presence of imprecise data in ontologies, aggregation operators play an important role in the decision making process. In this paper we present new definitions of ordered weighted averaging distance (OWAD) operators for interval-valued fuzzy numbers (IVFN) and show that...
This paper introduces a spatiotemporal data aggregation scheme using a novel networked fuzzy belief rule-based (NF-BRB) system. The proposed NF-BRB system is employed to design a decision support tool for relative water quality assessment in the distribution network. Different nodes of the network are grouped in several strata with the connectivity of the nodes shown using a spanning tree. For each...
This paper presents a quantitative decision making methodology for evaluating best alternative using benefits, opportunities, costs, and risks (BOCR) models together with the interval computation. The quantification using BOCR-interval arithmetic modeling is performed in association with two types of models: analytic network process (ANP) and analytic hierarchy process (AHP) via consensus of multiple...
We consider the problem of characterizing and computing a minimal context for a given fuzzy context. That is, for a given binary fuzzy relation between a set of objects and a set of attributes, we want to obtain a new fuzzy relation in such a way that its concept lattice is isomorphic to the concept lattice of the original fuzzy relation and such that the new fuzzy relation is minimal. It turns out...
Effectively managing risk is an essential element of successful project management. It is imperative that project management team consider all possible risks to establish corrective actions in the right time. So far, several techniques have been proposed for project risk analysis. Failure Mode and Effect Analysis (FMEA) is recognized as one of the most useful techniques in this field. The main goal...
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