Attempts Prediction by Missing Data Imputation in Engineering Degree

Jove, Esteban; Blanco-Rodríguez, Patricia; Casteleiro‐Roca, José‐Luis; Moreno-Arboleda, Javier; López-Vázquez, José Antonio; Juez, Francisco Javier de Cos; Calvo-Rolle, José Luís

doi:10.1007/978-3-319-67180-2_16

Cited by 18 publications

(8 citation statements)

References 32 publications

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“…For the current prediction in this paper, several regression techniques had been checked. The algorithms based on multiple regression analysis are accepted regression methods used in several applications [32][33][34][35][36][37]. Some previous works have shown the use of these methods despite its low performance [33,[38][39][40].…”

Section: Fuel Outputmentioning

confidence: 99%

Fuel Cell Output Current Prediction with a Hybrid Intelligent System

et al. 2019

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A fuel cell is a complex system, which produces electricity through an electrochemical reaction. For the formal application of control strategies on a fuel cell, it is very important to have a precise dynamic model of it. In this paper, a dynamic model of a real hydrogen fuel cell is obtained to predict its response. The data used in this paper to obtain the model have been acquired from a real fuel cell subjected to different load patterns by means of a programmable electronic load. Using this data, a nonlinear model based on a hybrid intelligent system is obtained. This hybrid model uses artificial neural networks to predict the output current of the fuel cell in a very precise way. The use of a hybrid scheme improves the performance of neural networks reducing to half the mean squared error obtained for a global model of the fuel cell.

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Section: Fuel Outputmentioning

confidence: 99%

Fuel Cell Output Current Prediction with a Hybrid Intelligent System

et al. 2019

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“…Además son numerosos los trabajos en los que se trata de valorar el rendimiento, como paso previo a la aplicación de técnicas de innovación, como muestra de ello se tienen los trabajos (López-Vázquez et al, 2015), (Crespo-Turrado et al, 2016), (Jove, Blanco-Rodríguez, et al, 2018), (Alaiz-Moretón et al, 2019), (Crespo-Turrado et al, 2020), (Jove et al, 2019), .…”

Section: Introductionunclassified

Experiencia de docencia basada en proyectos usando la música como elemento principal para la asignatura de Fundamentos de Electrónica

Quintián¹,

Jove²,

Casteleiro‐Roca³

et al. 2020

Contextos Universitarios Transformadores: Boas Prácticas No Marco Dos GID. IV Xornadas De Innovación Docente

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La tendencia actual y futura en las carreras técnicas y en especial en las ingenierías, es que el número de alumnos se ve cada vez más reducido, bien por falta de vocación o motivación para afrontar una carrera si bien compleja, con una alta demanda laboral. Parte de esa falta de motivación proviene muchas veces de la necesidad de convertir muchos de los contenidos en temáticas más atractivas para los estudiantes. Por ello en esta experiencia de innovación docente, se ha planteado el uso de la música como principal elemento motivador para convertir el mismo contenido de asignaturas, en especial de los primeros cursos, en contenidos más atractivos a los estudiantes y conseguir de este modo, no solo un mayor efecto de motivación sino también que esto se refleje en los resultados finales obtenidos por los estudiantes. En este caso en concreto, se propone el desarrollo e implementación de un circuito electrónico capaz de "buscar" una canción "escondida" entre otras muchas, de modo que se incluye además un aspecto competitivo entre los alumnos. Tras la experiencia, los resultados obtenidos han sido muy positivos, tanto en el aspecto motivacional con un aumento de la participación de los estudiantes en un 22%, así como en los resultados académicos obtenidos.

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“…The well‐known support vector machine algorithm employed in many different applications (Schölkopf et al, ; Calvo‐Rolle et al, ; Casteleiro‐Roca et al, ; Jove et al, ) is frequently used to solve the one‐class classification problem as well as support vector data description (Tax, ). To solve anomalies issues in different parts of industrial plants, the use of virtual sensors or missing data imputation techniques is very common (Casteleiro‐Roca et al, ; Fernández‐Serantes et al, ; Jove et al, ; Casteleiro‐Roca et al, ; Gonzalez‐Cava et al, ).…”

Section: Introductionmentioning

confidence: 99%

A fault detection system based on unsupervised techniques for industrial control loops

et al. 2019

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This research describes a novel approach for fault detection in industrial processes, by means of unsupervised and projectionist techniques. The proposed method includes a visual tool for the detection of faults, its final aim is to optimize system performance and consequently obtaining increased economic savings, in terms of energy, material, and maintenance. To validate the new proposal, two datasets with different levels of complexity (in terms of quantity and quality of information) have been used to evaluate five well‐known unsupervised intelligent techniques. The obtained results show the effectiveness of the proposed method, especially when the complexity of the dataset is high.

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Attempts Prediction by Missing Data Imputation in Engineering Degree

Cited by 18 publications

References 32 publications

Fuel Cell Output Current Prediction with a Hybrid Intelligent System

Fuel Cell Output Current Prediction with a Hybrid Intelligent System

Experiencia de docencia basada en proyectos usando la música como elemento principal para la asignatura de Fundamentos de Electrónica

A fault detection system based on unsupervised techniques for industrial control loops

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