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Representation of fuzzy knowledge bases using Petri nets: operation in the truth space.

Alberto Bugarín, Senén Barro (1996)

Mathware and Soft Computing

In this paper the execution of Fuzzy Knowledge Bases in the truth space is briefly analyzed. The computational efficiency of the process is significantly increased by means of a parameterized description based on the linguistic truth values described by Baldwin. This permits executing the Fuzzy Knowledge Base through operations involving only simple numerical values, thus avoiding the direct analytic manipulation of possibility distributions. A Petri Net-based formalism that permits representing...

Restricted ideals and the groupability property. Tools for temporal reasoning

J. Martínez, P. Cordero, G. Gutiérrez, I. P. de Guzmán (2003)

Kybernetika

In the field of automatic proving, the study of the sets of prime implicants or implicates of a formula has proven to be very important. If we focus on non-classical logics and, in particular, on temporal logics, such study is useful even if it is restricted to the set of unitary implicants/implicates [P. Cordero, M. Enciso, and I. de Guzmán: Structure theorems for closed sets of implicates/implicants in temporal logic. (Lecture Notes in Artificial Intelligence 1695.) Springer–Verlag, Berlin 1999]....

ReSySTER: A hybrid recommender system for Scrum team roles based on fuzzy and rough sets

Ricardo Colomo-Palacios, Israel González-Carrasco, José Luis López-Cuadrado, Ángel García-Crespo (2012)

International Journal of Applied Mathematics and Computer Science

Agile development is a crucial issue within software engineering because one of the goals of any project leader is to increase the speed and flexibility in the development of new commercial products. In this sense, project managers must find the best resource configuration for each of the work packages necessary for the management of software development processes in order to keep the team motivated and committed to the project and to improve productivity and quality. This paper presents ReSySTER,...

Right division in Moufang loops

Maria de Lourdes M. Giuliani, Kenneth Walter Johnson (2010)

Commentationes Mathematicae Universitatis Carolinae

If ( G , · ) is a group, and the operation ( * ) is defined by x * y = x · y - 1 then by direct verification ( G , * ) is a quasigroup which satisfies the identity ( x * y ) * ( z * y ) = x * z . Conversely, if one starts with a quasigroup satisfying the latter identity the group ( G , · ) can be constructed, so that in effect ( G , · ) is determined by its right division operation. Here the analogous situation is examined for a Moufang loop. Subtleties arise which are not present in the group case since there is a choice of defining identities and the identities produced by...

Rough membership functions: a tool for reasoning with uncertainty

Z. Pawlak, A. Skowron (1993)

Banach Center Publications

A variety of numerical approaches for reasoning with uncertainty have been investigated in the literature. We propose rough membership functions, rm-functions for short, as a basis for such reasoning. These functions have values in the interval [0,1] and are computable on the basis of the observable information about the objects rather than on the objects themselves. We investigate properties of the rm-functions. In particular, we show that our approach is intensional with respect to the class of...

Rough modeling - a bottom-up approach to model construction

Terje Loken, Jan Komorowski (2001)

International Journal of Applied Mathematics and Computer Science

Traditional data mining methods based on rough set theory focus on extracting models which are good at classifying unseen obj-ects. If one wants to uncover new knowledge from the data, the model must have a high descriptive quality-it must describe the data set in a clear and concise manner, without sacrificing classification performance. Rough modeling, introduced by Kowalczyk (1998), is an approach which aims at providing models with good predictive emphand descriptive qualities, in addition to...

Rough relation properties

Maria Nicoletti, Joaquim Uchoa, Margarete Baptistini (2001)

International Journal of Applied Mathematics and Computer Science

Rough Set Theory (RST) is a mathematical formalism for representing uncertainty that can be considered an extension of the classical set theory. It has been used in many different research areas, including those related to inductive machine learning and reduction of knowledge in knowledge-based systems. One important concept related to RST is that of a rough relation. This paper rewrites some properties of rough relations found in the literature, proving their validity.

Rough set-based dimensionality reduction for supervised and unsupervised learning

Qiang Shen, Alexios Chouchoulas (2001)

International Journal of Applied Mathematics and Computer Science

The curse of dimensionality is a damning factor for numerous potentially powerful machine learning techniques. Widely approved and otherwise elegant methodologies used for a number of different tasks ranging from classification to function approximation exhibit relatively high computational complexity with respect to dimensionality. This limits severely the applicability of such techniques to real world problems. Rough set theory is a formal methodology that can be employed to reduce the dimensionality...

Rough sets methods in feature reduction and classification

Roman Świniarski (2001)

International Journal of Applied Mathematics and Computer Science

The paper presents an application of rough sets and statistical methods to feature reduction and pattern recognition. The presented description of rough sets theory emphasizes the role of rough sets reducts in feature selection and data reduction in pattern recognition. The overview of methods of feature selection emphasizes feature selection criteria, including rough set-based methods. The paper also contains a description of the algorithm for feature selection and reduction based on the rough...

Rule-based fuzzy object similarity.

Horst Bunke, Xavier Fábregas, Abraham Kandel (2001)

Mathware and Soft Computing

A new similarity measure for objects that are represented by feature vectors of fixed dimension is introduced. It can simultaneously deal with numeric and symbolic features. Also, it can tolerate missing feature values. The similarity measure between two objects is described in terms of the similarity of their features. IF-THEN rules are being used to model the individual contribution of each feature to the global similarity measure between a pair of objects. The proposed similarity measure is based...

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