Evolvable fuzzy systems: some insights and challenges

Pedrycz, Witold

doi:10.1007/s12530-010-9002-1

Cited by 32 publications

(13 citation statements)

References 28 publications

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“…This structure gives a snapshot of a situation at a specific time. To accommodate SA L3 requirements for the projection phase, we can leverage on the concept of evolvable granules (Antonelli et al 2016;Pedrycz 2010).…”

Section: Evolving Situationsmentioning

confidence: 99%

A granular computing framework for approximate reasoning in situation awareness

2016

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We present our results on the adoption of a set-theoretic framework for granular computing to situation awareness. The proposed framework guarantees a high degree of flexibility in the process of creation of granules and granular structures allowing to satisfy the wide variety of requirements for perception and comprehension of situations where some elements must be perceived per similarity, others per spatial proximity, some must be fused to improve their comprehension, and so on. A second value is the support for approximate reasoning in situation awareness. A granular structure in particular represents a snapshot of a situation, and is a building block for the development of tools and techniques to reason on situation in order to reduce situation awareness errors and accelerate the process of decision-making. To this purpose, we show a technique to support operators in the analysis of conformity between a recognized situation and an expected one. A third value is the fact that we can support operators in having rapid and indicative measures of how two situations, e.g. a recognized and a projected, may differ. A preliminary evaluation instantiating our approach with self-organizing maps is reported and discussed. The results are encouraging with respect to the capability of improving perception and comprehension of a situation, reducing comprehension errors and supporting projection of situations

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Section: Evolving Situationsmentioning

confidence: 99%

A granular computing framework for approximate reasoning in situation awareness

2016

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“…In the presence of dynamically collected data, information granules move around, become refined, generalized and continuously changed (Pedrycz 2010). As a result, the structural continuity fluctuates and evolves in a continuous, smooth manner from one model to another.…”

Section: Text Identificationmentioning

confidence: 99%

A comparative study of evolving fuzzy grammar and machine learning techniques for text categorization

et al. 2014

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Several methods have been studied in text categorization and mostly are inspired by the statistical distribution features in the texts, such as the implementation of Machine Learning (ML) methods. However, there is no work available that investigates the performance of ML-based methods against the text expression-based method, especially for incident and medical case categorization. Meanwhile, these two domains are becoming ever more popular, due to a growing interest of automation in security intelligence and health services. This paper presents a text expression-based method called Evolving Fuzzy Grammar (EFG) and evaluates its performance against the conventional ML methods of Naïve Bayes, support vector machine, k-nearest neighbor, adaptive booting, and decision tree. The incident dataset used is a real dataset that was taken from the World Incidents Tracking System, while ImageCLEF 2009 was used as the source for radiology case reports. The results suggested variations of strength and weakness of each method in both cateCommunicated by V. Loia. gorization tasks, where a standard evaluation technique (i.e., recall, precision, and F-measure) was used. In both domains, the SMO and IBk methods were the best, while AdaBoost was the worst. It was also observed that the medical dataset was easier to categorize than the incident. Although EFG was ranked second lowest, it obtained the highest precision score in the bombing categorization, the highest score in armed attack recall, and was averagely ranked in the top three for the medical case categorization. It was also noted that the text expression-based method used in EFG was the most verbose and expressive, when compared to the ML methods. This indicates that EFG is a viable method in text categorization and may serve as an alternative approach to such a task.

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“…Se probó que el modelo matemático propuesto que describe el proceso de frenado de una motocicleta es asintótico estable. En el futuro, se van a proponer un observador y un control para mejorar el frenado de una motocicleta, y se va a proponer un identificador diseñado con la tecnica de los sistemas inteligentes envolventes [4], [10], [12], [14], [21], [22], [23].…”

Section: Simulación Con Datos Realesunclassified

Comparison of four mathematical models for braking of a motorcycle

Rubio

Torres

Rivera

et al. 2011

IEEE Latin Am. Trans.

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The major contributions of this paper are as follows: 1) four mathematical models that are used to describe the motorcycle dynamics during braking are presented, the first three are obtained from previous papers and the fourth is proposed in this paper 2) the differences between the four mathematical models are described, 3) It is proven that the proposed mathematical model used to describe the motorcycle dynamics during braking is asymptotic astable, 4) a comparison between the four mathematical models is presented based in two facts: a) the relative velocity has to be positive during braking, and b) real data are obtained from a motorcycle and used in the comparisons. Keywords-Bracking process, motorcycle, mathematical model. I. INTRODUCCION XISTEM algunas investigaciones sobre modelos matematicos como son [1], [3], [15], [20], [26], y [28]. En [1] se propone una arquitectura de control inteligente que mitiga la necesidad de un conocimiento exacto del valor del retardo, el esquema de control inteligente está compuesto por un conjunto de modelos con retardos distintos operando en paralelo. En [3], ellos presentan un modelo matematico de las transacciones de un negocio dividido en dos vistas, una organizacional y la otra de procesos de negocio. En [15], han desarrollado expresiones analticas cerradas, para los parámetros que caracterizan la estadstica de desvanecimiento en frecuencia de canal UWB. En [20], ellos presentan la aproximacion usando algoritmos geneticos de un modelo termico desarrollado por el MIT en 1997. El trabajo de [26] presenta una herramienta de software que brinda soporte a la generacion de modelos neuronales directamente desde las mediciones. En [28], ellos presentan el control del modelo cinemático del robot móvil usando linealización entrada-salida por realimentación estática. Los trabajos previos nos ilustran que hay dos tipos de modelos matematicos, unos son los analitcos usados en [1], [3], [15], [28] y los otros son los modelos numericos usados en [20], [26]. En este articulo se va a trabajar con los modelos matematicos analiticos. Existe algunos trabajos sobre vehculos. El articulo de [11] analiza la respuesta dinamica de una motocicleta con un freno ABS y una camara. En [16], se propone un modelo de friccion para la emulacion dinamica de la fricción camino/rueda para validar el diseño de un control. El trabajo de [8] proporciona un resumen de los ultimos avances en el diseño de la suspención de vehiculos terrestres, su dinamica y el control, junto con las perspectivas del autor. En [27], ellos desarrollan un modelo de dinámicas multicuerpo para un carro equipado con una estructura de suspención McPerson, al cual le aplican una técnica de identificación. El trabajo de [17] discute las dinámicas de un motor-a-deslizamiento de una motocicleta las cuales estan relacionadas al diseño de control de tracción. En este articulo se va a trabajar el caso del sistema de frenos.El modelo matemático del proceso de frenado describe la relación entre la fricción interna, la velocidad lineal de la rue...

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Evolvable fuzzy systems: some insights and challenges

Cited by 32 publications

References 28 publications

A granular computing framework for approximate reasoning in situation awareness

A granular computing framework for approximate reasoning in situation awareness

A comparative study of evolving fuzzy grammar and machine learning techniques for text categorization

Comparison of four mathematical models for braking of a motorcycle

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