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Rubio, G.A., Agila, W.E |
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A fuzzy model to manage water in polymer electrolyte membrane fuel cells |
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Journal Article |
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2021 |
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In Processes Journal. (Article number 904) |
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Vol. 9 |
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Issue 6 |
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PEM fuel cell, fuzzy, neural network, electrical response, flooding, drying. |
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Abstract |
In this paper, a fuzzy model is presented to determine in real-time the degree of dehydration or flooding of a proton exchange membrane of a fuel cell, to optimize its electrical response and consequently, its autonomous operation. By applying load, current and flux variations in the dry, normal, and flooded states of the membrane, it was determined that the temporal evolution of the fuel cell voltage is characterized by changes in slope and by its voltage oscillations. The results were validated using electrochemical impedance spectroscopy and show slope changes from 0.435 to 0.52 and oscillations from 3.6 mV to 5.2 mV in the dry state, and slope changes from 0.2 to 0.3 and oscillations from 1 mV to 2 mV in the flooded state. The use of fuzzy logic is a novelty and constitutes a step towards the progressive automation of the supervision, perception, and intelligent control of fuel cells, allowing them to reduce their risks and increase their economic benefits. |
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no |
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cidis @ cidis @ |
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153 |
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Author |
Rafael E. Rivadeneira, Angel Domingo Sappa, Vintimilla B. X. and Hammoud R. |
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Title |
A Novel Domain Transfer-Based Approach for Unsupervised Thermal Image Super- Resolution. |
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Journal Article |
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2022 |
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Sensors |
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Sensors |
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Vol. 22 |
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Issue 6 |
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cidis @ cidis @ |
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170 |
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Daniela Rato, Miguel Oliviera, Victor Santos, Manuel Gomes & Angel Sappa |
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A Sensor-to-Pattern Calibration Framework for Multi-Modal Industrial Collaborative Cells. |
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Journal Article |
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2022 |
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Journal of Manufacturing Systems |
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Vol. 64 |
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pp. 497-507 |
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yes |
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cidis @ cidis @ |
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184 |
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Del Pino, J.; Salazar, G.; Cedeño, V. Msc. |
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Title |
Adaptación de un Recomendador de Filtro Colaborativo Basado en el Usuario para la Creación de un Recomendador de Materias de Pregrado Basado en el Historial Académico de los Estudiantes |
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Journal Article |
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2011 |
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Revista Tecnológica ESPOL |
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Vol. 24 |
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pp. 29 - 34 |
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Los sistemas de recomendación son ampliamente utilizados hoy en día gracias a su capacidad de analizar las preferencias de usuarios y sugerir ítems. No obstante, el uso de los recomendadores está limitado a un modelo basado en el usuario y no en su historial de preferencias, discriminando así el campo de aplicación, por ejemplo, a sistemas académicos donde sea primordial el estudio de las decisiones del estudiante a lo largo de su carrera. El presente
trabajo presenta un esfuerzo por adaptar filtros colaborativos basados en el usuario a filtros colaborativos basados en el historial del usuario. Con un conjunto de pruebas mediremos su efectividad utilizando dos algoritmos distintos de similaridad para recomendar materias a un estudiante en el sexto semestre de la carrera de Ingeniería en Electrónica y Telecomunicaciones ofertada por la FIEC – ESPOL. Los resultados muestran que es factible adaptar un recomendador a un modelo basado en el historial del usuario |
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Campus “Gustavo Galindo Velasco” La prosperina Km 30,5 vía perimetral, Guayaquil, Ecuador |
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Español |
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Español |
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cidis @ cidis @ |
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13 |
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