Displaying similar documents to “Operating on formal concept abstraction.”

Contributions to the symbolic processing of segments in computer vision.

Jorge Cabrera, Francisco M. Hernández, Antonio Falcón, Juan Méndez (1996)

Mathware and Soft Computing

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In this paper a processing methodology is introduced for the segment or intermediate level in the context of knowledge-based computer vision systems. The proposed methodology demonstrates how using simple Fuzzy Logic concepts it is possible to associate symbolic descriptions to the entities of this level. It provides with the basic mechanisms for performing symbolic computation, evidence combination, uncertainty management and spatial reasoning at the segment level.

Improvement to the cooperative rules methodology by using the ant colony system algorithm.

Rafael Alcalá, Jorge Casillas, Oscar Cordón, Francisco Herrera (2001)

Mathware and Soft Computing

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The cooperative rules (COR) methodology [2] is based on a combinatorial search of cooperative rules performed over a set of previously generated candidate rule consequents. It obtains accurate models preserving the highest interpretability of the linguistic fuzzy rule-based systems. Once the good behavior of the COR methodology has been proven in previous works, this contribution focuses on developing the process with a novel kind of metaheuristic algorithm: the ant colony system one....

A survey of methods to evaluate quantified sentences.

Miguel Delgado, Daniel Sánchez, José María Serrano, M. Amparo Vila (2000)

Mathware and Soft Computing

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The evaluation of quantified sentences is used to solve several problems. Most of the methods proposed in the literature are not satisfactory because they do not verify some intuitive properties. In this paper we propose an extension of both possibilistic and probabilistic methods, based on the Sugeno and the Choquet fuzzy integrals respectively, for the evaluation of type II sentences, the most general kind of sentences. These methods verify good properties, and they are shown to be...

Rough membership functions: a tool for reasoning with uncertainty

Z. Pawlak, A. Skowron (1993)

Banach Center Publications

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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...

Fuzzy clustering: Insights and new approach.

Frank Klawonn (2004)

Mathware and Soft Computing

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Fuzzy clustering extends crisp clustering in the sense that objects can belong to various clusters with different membership degrees at the same time, whereas crisp or deterministic clustering assigns each object to a unique cluster. The standard approach to fuzzy clustering introduces the so-called fuzzifier which controls how much clusters may overlap. In this paper we illustrate, how this fuzzifier can help to reduce the number of undesired local minima of the objective function that...

Some practical problems in fuzzy sets-based decision support systems.

Alejandro Sancho-Royo, José Luis Verdegay, Edmundo Vergara-Moreno (1999)

Mathware and Soft Computing

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In this paper some problems arising in the interface between two different areas, Decision Support Systems and Fuzzy Sets and Systems, are considered. The Model-Base Management System of a Decision Support System which involves some fuzziness is considered, and in that context the question, first, of the practical determination of membership functions, second of the management of the fuzziness in some optimisation models, and finally of using fuzzy rules for terminating conventional...