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scopus(14)
A new paradigm for uncertain knowledge representation by Plausible Petri nets
ArticleAbstract: This paper presents a new model for Petri nets (PNs) which combines PN principles with the foundatioPalabras claves:Expert systems, information theory, Knowledge Representation, Petri netsAutores:Andrews J., Juan Chiachío, Prescott D., Ruano M.C.Fuentes:scopusA panoramic view and swot analysis of artificial intelligence for achieving the sustainable development goals by 2030: progress and prospects
ArticleAbstract: The17 Sustainable Development Goals (SDGs) established by the United Nations Agenda 2030 constitutePalabras claves:Artificial Intelligence, Emerging digital technologies, SUSTAINABLE DEVELOPMENT GOALSAutores:Alonso S., de Vargas J.P., Fernández B., García-Moral P., Herrera F., Juan Chiachío, Marchena R., Martínez-Cámara E., Melero F.J., Molina D., Montes R., Moral C., Palomares I., Ruano M.C.Fuentes:scopusBayesian damage localization and identification based on a transient wave propagation model for composite beam structures
ArticleAbstract: This paper proposes the use of a physics-based Bayesian framework for the localization and identificPalabras claves:Bayesian inverse problem, Composite beams, Guided waves, Structural Health Monitoring, Ultrasound, Wave and finite element methodAutores:Cantero-Chinchilla S., Chronopoulos D., Juan Chiachío, Malik M.K.Fuentes:scopusAn information theoretic approach for knowledge representation using Petri nets
Conference ObjectAbstract: A new hybrid approach for Petri nets (PNs) is proposed in this paper by combining the PNs principlesPalabras claves:Expert systems, Knowledge Representation, Petri netsAutores:Andrews J., Juan Chiachío, Prescott D., Ruano M.C.Fuentes:scopusAn inverse-problem based stochastic approach to model the cumulative damage evolution of composites
Conference ObjectAbstract: Fibre-reinforced composites are often selected for high-responsibility structural applications due tPalabras claves:Composite laminates, Damage accumulation, Inverse Problem, Markov chains, Unitary-time-transformationAutores:Juan Chiachío, Ruano M.C., Rus G.Fuentes:scopusAdaptive approximate Bayesian computation by subset simulation for structural model calibration
ArticleAbstract: This paper provides a new approximate Bayesian computation (ABC) algorithm with reduced hyper-paramePalabras claves:Autores:Frank Cabanilla, José Barros, Juan Chiachío, Ruano M.C.Fuentes:scopusApproximate bayesian computation by subset simulation
ArticleAbstract: A new approximate Bayesian computation (ABC) algorithm for Bayesian updating of model parameters isPalabras claves:Approximate Bayesian Computation, Bayesian inverse problem, Subset simulationAutores:Beck J.L., Juan Chiachío, Ruano M.C., Rus G.Fuentes:scopusStructural digital twin framework: Formulation and technology integration
ArticleAbstract: This work presents a digital twin framework for structural engineering. The digital twin is conceptuPalabras claves:Bayesian learning, DIGITAL TWIN, internet of things, Petri nets, Structural Health MonitoringAutores:Fernández J., Jalón M.L., Juan Chiachío, Megía M., Ruano M.C.Fuentes:scopusUncertainty quantification in Neural Networks by Approximate Bayesian Computation: Application to fatigue in composite materials
ArticleAbstract: Modern machine learning algorithms excel in a great variety of tasks, but at the same time, it is alPalabras claves:Approximate Bayesian Computation, Bayesian Neural Network, Gradient-free training, Non-parametric formulation, Subset simulation, uncertainty quantificationAutores:Fernández J., Herrera F., Juan Chiachío, Munoz R., Ruano M.C.Fuentes:scopusOptiSens—Convex optimization of sensor and actuator placement for ultrasonic guided-wave based structural health monitoring
ArticleAbstract: This paper presents OptiSens, a computational platform in Python and Matlab, that provides optimal sPalabras claves:Cost–benefit optimization, Optimal sensor placement, Structural Health Monitoring, Ultrasonic guided-wavesAutores:Beck J.L., Cantero-Chinchilla S., Chronopoulos D., Juan Chiachío, Ruano M.C.Fuentes:scopus