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From ignorance to uncertainty: a conceptual analysis

Pietro Baroni, Giovanni Guida, Silvano Mussi (1998)

Kybernetika

This paper aims to develop an analysis of how ignorance affects the reasoning activity and is related to the concept of uncertainty. With reference to a simple inferential reasoning step, involving a single piece of relational knowledge, we identify four types of ignorance and show how they give rise to different types of uncertainty. We then introduce the concept of reasoning attitude, as a basic choice about how reasoning should be carried out in presence of ignorance. We identify two general...

FSP and FLTL framework for specification and verification of middle-agents

Amelia Bădică, Costin Bădică (2011)

International Journal of Applied Mathematics and Computer Science

Agents are a useful abstraction frequently employed as a basic building block in modeling service, information and resource sharing in global environments. The connecting of requester with provider agents requires the use of specialized agents known as middle-agents. In this paper, we propose a formal framework intended to precisely characterize types of middle-agents with a special focus on matchmakers, brokers and front-agents by formally modeling their interactions with requesters and providers....

Function approximation of Seidel aberrations by a neural network

Rossella Cancelliere, Mario Gai (2004)

Bollettino dell'Unione Matematica Italiana

This paper deals with the possibility of using a feedforward neural network to test the discrepancies between a real astronomical image and a predefined template. This task can be accomplished thanks to the capability of neural networks to solve a nonlinear approximation problem, i.e. to construct an hypersurface that approximates a given set of scattered data couples. Images are encoded associating each of them with some conveniently chosen statistical moments, evaluated along the x , y axes; in this...

Fuzzy approach for data association in image tracking.

Julio García, José Manuel Molina, Juan Alberto Besada, Javier I. Portillo (2003)

Mathware and Soft Computing

A fuzzy system has been developed to ponder update decisions both for the trajectories and shapes estimated for targets. It is embedded in an A-SMGCS Surveillance function for airport surface, based on video data processing, in charge of the automatic detection, identification and tracking of all interesting targets (aircraft and relevant ground vehicles). The tracking system captures a sequence of images, preprocesses them to extract the moving regions (blobs), and associates the blobs to tracks...

Fuzzy approximation relations, modal structures and possibilistic logic.

Francesc Esteva, Pere García, Lluis. Godo, Ricardo O. Rodríguez (1998)

Mathware and Soft Computing

The paper introduces a general axiomatic notion of approximation mapping, a mapping that associates to each crisp proposition p a fuzzy set representing approximately p. It is shown how it can be obtained through fuzzy relations, which are at least reflexive. We study the corresponding multi-modal systems depending on the properties satisfied by the approximate relation. Finally, we show some equivalences between possibilistic logical consequences and global/local logical consequences in the multi-modal...

Fuzzy clustering: Insights and new approach.

Frank Klawonn (2004)

Mathware and Soft Computing

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 is associated...

Fuzzy clustering of fuzzy data considering the shape of the membership functions using a novel representation learning technique

Alireza Khastan, Elham Eskandari (2025)

Kybernetika

Most existing distance measures for fuzzy data do not capture differences in the shapes of the left and right tails of membership functions. As a result, they may calculate a distance of zero between fuzzy data even when these differences exist. Additionally, some distance measures cannot compute distances between fuzzy data when their membership functions differ in type. In this paper, inspired by human visual perception, we propose a fuzzy clustering method for fuzzy data using a novel representation...

Fuzzy controller for obstacle-avoidance with a non-holonomous mobile robot.

Uribe 1, Juan Pedro, Joseba Urzelai (1998)

Mathware and Soft Computing

This paper describes the design and development of a sensor based navigation system which makes it possible for a non-holonomous mobile robot to avoid obstacles using information on its environment picked up by a belt of ultrasonic sensors. To control the robot no preliminary information regarding its environment is required, the robot adapts to them through the information gathered on the spot by the ultrasonic sensors and the information released from a spatial memory. The controller, which allows...

Fuzzy decision trees to help flexible querying

Christophe Marsala (2000)

Kybernetika

Fuzzy data mining by means of the fuzzy decision tree method enables the construction of a set of fuzzy rules. Such a rule set can be associated with a database as a knowledge base that can be used to help answering frequent queries. In this paper, a study is done that enables us to show that classification by means of a fuzzy decision tree is equivalent to the generalized modus ponens. Moreover, it is shown that the decision taken by means of a fuzzy decision tree is more stable when observation...

Fuzzy grammatical inference using neural network.

Armando Blanco, A. Delgado, M. Carmen Pegalajar (1998)

Mathware and Soft Computing

We have shown a model of fuzzy neural network that is able to infer the relations associated to the transitions of a fuzzy automaton from a fuzzy examples set. Neural network is trained by a backpropagation of error based in a smooth derivative [1]. Once network has been trained the fuzzy relations associated to the transitions of the automaton are found encoded in the weights.

Fuzzy inference using a least square model.

Humberto Bustince, M. Calderón, Victoria Mohedano (1998)

Mathware and Soft Computing

In this paper, the method of least squares is applied to the fuzzy inference rules. We begin studying the conditions in which from a fuzzy set we can build another through the method of least squares. Then we apply this technique in order to evaluate the conclusions of the generalized modus ponens. We present different theorems and examples that demonstrate the fundamental advantages of the method studied.

Fuzzy max-min classifiers decide locally on the basis of two attributes.

Birka von Schmidt, Frank Klawonn (1999)

Mathware and Soft Computing

Fuzzy classification systems differ from fuzzy controllers in the form of their outputs. For classification problems a decision between a finite number of discrete classes has to be made, whereas in fuzzy control the output domain is usually continuous, i.e. a real interval. In this paper we consider fuzzy classification systems using the max-min inference scheme and classifying an unknown datum on the basis of maximum matching, i.e. assigning it to the class appearing in the consequent of the rule...

Fuzzy multicriteria decision making applied to the strategic plan of Valencia.

Ana M. Nieto Morote, Francisco Ruz Vila (2002)

Mathware and Soft Computing

We present a fuzzy multicriteria decision making to get the ranking of several projects presented to the major council of Valencia whose final aim is to define the future urbanistic structure of the city. This technique allows us to deal with such problems that are defined by linguistic (and vague) terms, like the case mentioned below.

Fuzzy neural network approach to fuzzy polynomials.

Saeid Abbasbandy, M. Otadi (2006)

Mathware and Soft Computing

In this paper, an architecture of fuzzy neural networks is proposed to find a real root of a dual fuzzy polynomial (if exists) by introducing a learning algorithm. We proposed a learning algorithm from the cost function for adjusting of crisp weights. According to fuzzy arithmetic, dual fuzzy polynomials can not be replaced by a fuzzy polynomials, directly. Finally, we illustrate our approach by numerical examples.

Fuzzy querying: issues and perspectives

Janusz Kacprzyk, Gabriella Pasi, Peter Vojtáš, Sławomir Zadrożny (2000)

Kybernetika

The term query is widely used in the database as well as information retrieval communities. Basically, a query against a collection of information items (to be called later, for brevity, an information source) provides a formal description of the items of interest to the user posing this query. A source of information is meant here very generally. It may take the form of an archive of multimedia or textual documents, a database, or a knowledge base. In the three previous examples the information...

Fuzzy set theory for cumulative trauma prediction.

Daniel J. Fonseca, Thomas W. Merritt, Gary P. Moynihan (2001)

Mathware and Soft Computing

A widely used fuzzy reasoning algorithm was modified and implemented via an expert system to assess the potential risk of employee repetitive strain injury in the workplace. This fuzzy relational model, known as the Priority First Cover Algorithm (PFC), was adapted to describe the relationship between 12 cumulative trauma disorders (CTDs) of the upper extremity, and 29 identified risk factors. The algorithm, which finds a suboptimal subset from a group of variables based on the criterion of priority,...

Fuzzy sets in computer vision: an overview.

Pilar Sobrevilla, Eduard Montseny (2003)

Mathware and Soft Computing

Every computer vision level crawl with uncertainty, what makes its management a significant problem to be considered and solved when trying for automated systems for scene analysis and interpretation. This is why fuzzy set theory and fuzzy logic is making many inroads into the handling of uncertainty in various aspects of image processing and computer vision.The growth within the use of fuzzy set theory in computer vision is keeping pace with the use of more complex algorithms addressed to solve...

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