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Uncertainty propagation in fuzzy grey cognitive maps with hebbian-like learning algorithms

Salmeron J.L.; Palos-Sanchez P.R. (Institute of Electrical and Electronics Engineers Inc., 2019)

Uncertainty Propagation in Fuzzy Grey Cognitive Maps With Hebbian-Like Learning Algorithms

Salmerón, José L (1); Palos-Sánchez, Pedro R

This paper is focused on an innovative fuzzy cognitive maps extension called fuzzy grey cognitive maps (FGCMs). FGCMs are a mixture of fuzzy cognitive maps and grey systems theory. These have become a useful framework for ...

Aplicação de máquinas de aprendizado extremo ao problema de aprendizado ativo

Euler Guimarães Horta (Universidade Federal de Minas GeraisUFMG, 2015-10-07)

The main objective of Active Learning is to choose only the most informative patterns to be labeled and learned. In Active Learning scenario a selection strategy is used to analyze a non-labeled pattern and to decide whether ...

Gradient-based Algorithms For The Automatic Construction Of Fuzzy Cognitive Maps

Madeiro S.S.; Zuben F.J.V. (, 2012)

BEHAVIOR ANALYSIS AND ARTIFICIAL NEURAL NETWORKSANÁLISIS CONDUCTUAL y REDES NEURALES ARTIFICIALES

POTTER, BILL; CALIFORNIA STATE UNIVERSITY; WILSON, MICHAEL; CALIFORNIA STATE UNIVERSITY (Sociedad Mexicana de Análisis de la Conducta / Mexican Society of Behavior Analysis, 2011)

Uma Rede Neural Auto-Organizável Construtiva para Aprendizado Perpétuo de Padrões Espaço-TemporaisA growing self-organizing neural network for lifelong learning of spatiotemporal patterns

Bastos, Eduardo Nunes Ferreira (2008)

Vehicle recognition by using acoustic signature and classic DSP techniques

Díaz Velásquez, María Fernanda; Guerrero Ramírez, Jorge Eduardo

Efectos de la estructura estadística de los datos en la implementación de la red neuronal autosupervisadaEffects of statistical data structure on the implementation of a self-supervised neural network

Sánchez Alvarado, Luis Alberto; Huamanchumo De la Cuba, Luis Emilio; Sánchez Alvarado, Luis Alberto (Universidad Nacional de Ingeniería, 2018)

Efectos de la estructura estadística de los datos en la implementación de la red neuronal autosupervisadaEffects of statistical data structure on the implementation of a self-supervised neural network

Sánchez Alvarado, Luis Alberto; Huamanchumo De la Cuba, Luis Emilio; Sánchez Alvarado, Luis Alberto (Universidad Nacional de Ingeniería, 2018)

Modelo de detección de intrusiones en sistemas de red, realizando selección de características con FDR y entrenamiento y clasificación con SOMIntrusion detection model in network systems, making feature selection with fdr and classification-training stages with s

De-La-Hoz-Franco, Emiro; De la Hoz Correa, Eduardo Miguel; Ortiz, Andrés; Ortega, Julio (Corporación Universidad de la Costa, 2019)

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Uncertainty propagation in fuzzy grey cognitive maps with hebbian-like learning algorithms

Uncertainty Propagation in Fuzzy Grey Cognitive Maps With Hebbian-Like Learning Algorithms

Aplicação de máquinas de aprendizado extremo ao problema de aprendizado ativo

Gradient-based Algorithms For The Automatic Construction Of Fuzzy Cognitive Maps

BEHAVIOR ANALYSIS AND ARTIFICIAL NEURAL NETWORKSANÁLISIS CONDUCTUAL y REDES NEURALES ARTIFICIALES

Uma Rede Neural Auto-Organizável Construtiva para Aprendizado Perpétuo de Padrões Espaço-TemporaisA growing self-organizing neural network for lifelong learning of spatiotemporal patterns

Vehicle recognition by using acoustic signature and classic DSP techniques

Efectos de la estructura estadística de los datos en la implementación de la red neuronal autosupervisadaEffects of statistical data structure on the implementation of a self-supervised neural network

Efectos de la estructura estadística de los datos en la implementación de la red neuronal autosupervisadaEffects of statistical data structure on the implementation of a self-supervised neural network

Modelo de detección de intrusiones en sistemas de red, realizando selección de características con FDR y entrenamiento y clasificación con SOMIntrusion detection model in network systems, making feature selection with fdr and classification-training stages with s