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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)(3)
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A simulation algorithm for multienvironment probabilistic P systems: A formal verification
ArticleAbstract: Multienvironment probabilistic P systems provide a framework of specification for modeling populatioPalabras claves:Biological modeling, Formal verification, P systemsAutores:Fernando Sancho-Caparrini, Martínez-del-Amor M., Pérez-Hurtado I., Pérez-Jiménez M.J., Riscos-Núñez A.Fuentes:scopusDecision P systems and the P≠NP conjecture
ArticleAbstract: We introduce decision P systems, which are a class of P systems with symbol-objects and external outPalabras claves:Autores:Fernando Sancho-Caparrini, Pérez-Jiménez M.J., Romero-Jiménez A.Fuentes:scopusDeep Form Finding Using Variational Autoencoders for deep form finding of structural typologies
Conference ObjectAbstract: In this paper, we are aiming to present a methodology for generation, manipulation and form findingPalabras claves:Artificial Intelligence, Deep Neural Networks, Form finding, generative design, Structural design, Variational autoencodersAutores:Fernando Sancho-Caparrini, Miguel J.d., Piškorec L., Villafañe M.E.Fuentes:scopusFrom fault detection to one-class severity discrimination of 3D printers with one-class support vector machine
ArticleAbstract: The lack of faulty condition data reduces the feasibility of supervised learning for fault detectionPalabras claves:3D printer, Bidirectional generative adversarial network, Fault Detection, One-Class Support Vector Machine, Severity discriminationAutores:Diego Cabrera Mendieta, Diego R. Cabrera, Estupinan E., Fernando Sancho-Caparrini, Li C., Mariela Cerrada Lozada, René-Vinicio Sánchez LojaFuentes:googlescopusFusing convolutional generative adversarial encoders for 3D printer fault detection with only normal condition signals
ArticleAbstract: Collecting data from mechanical systems in abnormal conditions is expensive and time consuming. ConsPalabras claves:3D printers, Adversarial learning, Condition-Based Maintenance, convolutional neural networks, Fault DetectionAutores:Diego Cabrera Mendieta, Diego R. Cabrera, Fernando Sancho-Caparrini, Li C., Long J., Mariela Cerrada Lozada, René-Vinicio Sánchez Loja, Valente de Oliveira J.Fuentes:googlescopusGeneration of geometric interpolations of building types with deep variational autoencoders
ArticleAbstract: This work presents a methodology for the generation of novel 3D objects resembling wireframes of buiPalabras claves:Artificial Intelligence, artificial neural networks, computer-aided architectural design, Computer-aided design, deep generative models, deep learning, Deep Neural Networks, form-finding, generative design, procedural design, Structural design, variational autoencoderAutores:Fernando Sancho-Caparrini, Miguel J.d., Piškorec L., Villafañe M.E.Fuentes:scopusGenerative Adversarial Networks Selection Approach for Extremely Imbalanced Fault Diagnosis of Reciprocating Machinery
ArticleAbstract: At present, countless approaches to fault diagnosis in reciprocating machines have been proposed, alPalabras claves:GaN, Imbalanced data, Model selection, random forest, reciprocating machineryAutores:Diego R. Cabrera, Fernando Sancho-Caparrini, Li C., Long J., Mariela Cerrada Lozada, René-Vinicio Sánchez Loja, Zhang S.Fuentes:scopusEcho state network and variational autoencoder for efficient one-class learning on dynamical systems
Conference ObjectAbstract: Usually, time series acquired from some measurement in a dynamical system are the main source of infPalabras claves:deep learning, Dynamical system modeling, reservoir computing, variational inferenceAutores:Diego Cabrera Mendieta, Diego R. Cabrera, Fernando Sancho-Caparrini, Mariela Cerrada Lozada, René-Vinicio Sánchez Loja, Tobar F.Fuentes:googlescopusImplementing in prolog an effective cellular solution to the knapsack problem
ArticleAbstract: In this paper we present an implementation in Prolog of an effective solution to the Knapsack problePalabras claves:Autores:Cordón-Franco A., Fernando Sancho-Caparrini, Gutiérrez-Naranjo M.A., Pérez-Jiménez M.J., Riscos-Núñez A.Fuentes:scopusKnowledge extraction from deep convolutional neural networks applied to cyclo-stationary time-series classification
ArticleAbstract: Modelling complex processes from raw time series increases the necessity to build Deep Learning (DL)Palabras claves:Convolutional neural network, Cyclo-stationary time-series analysis, deep learning, Fault diagnosis, Knowledge ExtractionAutores:Diego Cabrera Mendieta, Diego R. Cabrera, Fernando Sancho-Caparrini, Li C., Mariela Cerrada Lozada, René-Vinicio Sánchez LojaFuentes:googlescopus