Why triangular membership functions?

Pedrycz, Witold

doi:10.1016/0165-0114(94)90003-5

Cited by 664 publications

(262 citation statements)

References 2 publications

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“…Estructura del modelo difuso En la búsqueda de un equilibrio entre la aproximación numérica y la interpretabilidad del sistema difuso resultante se consideran los criterios siguientes para la selección de los parámetros [12] • Funciones de Pertenencia La partición de los universos de las variables de entrada en el proceso de aprendizaje se hace con conjuntos triangulares normalizados con solapamiento específico de 0.5. Las funciones de pertenencia triangulares permiten la reconstrucción del valor lingüístico en el mismo valor numérico, luego de aplicar un método de concreción [13]; además, el solapamiento en 0.5 asegura que los soportes de los conjuntos difusos sean diferentes.…”

Section: Identificación Difusaunclassified

Algoritmo para generación de Controladores Difusos Interpretables. Aplicación a un proceso de presión

Contreras¹,

Aldana²

2011

Iteckne

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Section: Identificación Difusaunclassified

Algoritmo para generación de Controladores Difusos Interpretables. Aplicación a un proceso de presión

Contreras¹,

Aldana²

2011

Iteckne

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“…The 2000s Hastak and Shaked (2000) AHP and Probability â Tah and Carr (2000) FST â Dey ( Pedrycz (1994) expressed that a triangular Fuzzy number (TFN) is the easiest and simplest way to approach the convex functions. Moreover, if the pairwise comparison process involves group-decision-making, the experts' preferences on particular criterion have to be aggregated.…”

Section: Pairwise Comparison To Establish Fuzzy Comparison Matrixmentioning

confidence: 99%

Design and Pilot Run of Fuzzy Synthetic Model (Fsm) for Risk Evaluation in Civil Engineering

Abdul‐Rahman

Chen

Lee

2013

Journal of Civil Engineering and Management

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Abstract. Most of the current construction risk assessment tools deliver unsatisfactory results because the prerequisite for their effective applications rely on the availability of high quality data especially during the early stage of a project. Unfortunately, such data are limited, ambiguous or even not exist due to the great uncertainty inherent in construction projects. Based on Fuzzy Synthetic Analysis (FSA), a model development team was formed among construction engineers, IT professionals, and Mathematicians in developing a holistic risk assessment model to estimate the construction risks especially for the situations with incomplete data and vague environments. Through qualitative scales defined by triangular fuzzy numbers used in pairwise comparisons to capture the vagueness in the linguistic variables, a risk assessment model using Analytic Hierarchy Process (AHP) was developed. The Pilot Run revealed the developed Fuzzy Synthetic Model (FSM) could accelerate the decisionmaking process and provide optimal allocation of project resources to mitigate possible risks detrimental to the success of a project in terms of time, cost, and quality.

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“…In particular, we apply weighting using a triangular fuzzy number function which reaches its maximum value of 1 for a feature at the centre of a wedge (i.e. in the bisecting direction from the centre of the coin) and its minimum of 0 at the centres of the two neighbouring wedges [21,22].…”

Section: Soft Wedge Siftmentioning

confidence: 99%

Ancient Roman Coin Retrieval: A Systematic Examination of the Effects of Coin Grade

Fare

Arandjelović

2017

Lecture Notes in Computer Science

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Abstract. Ancient coins are historical artefacts of great significance which attract the interest of scholars, and a large and growing number of amateur collectors. Computer vision based analysis and retrieval of ancient coins holds much promise in this realm, and has been the subject of an increasing amount of research. The present work is in great part motivated by the lack of systematic evaluation of the existing methods in the context of coin grade which is one of the key challenges both to humans and automatic methods. We describe a series of methods -some being adopted from previous work and others as extensions thereof -and perform the first thorough analysis to date.

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Why triangular membership functions?

Cited by 664 publications

References 2 publications

Algoritmo para generación de Controladores Difusos Interpretables. Aplicación a un proceso de presión

Algoritmo para generación de Controladores Difusos Interpretables. Aplicación a un proceso de presión

Design and Pilot Run of Fuzzy Synthetic Model (Fsm) for Risk Evaluation in Civil Engineering

Ancient Roman Coin Retrieval: A Systematic Examination of the Effects of Coin Grade

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