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Chiachío Ruano, Juan
74  Ergebnisse:
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1

Bayesian structural parameter identification from ambient v..:

Hernández Montes, Enrique ; Jalón Ramírez, María Lourdes ; Rodríguez Romero, Rubén...
Engineering Structures, 284 (115924)..  , 2023
Link: https://idus.us.es/handl..
 
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2

Bayesian structural parameter identification from ambient v..:

Hernández Montes, Enrique ; Jalón Ramírez, María Lourdes ; Chiachío Ruano, Juan.
nfo:eu-repo/grantAgreement/EC/821054.  , 2023
Link: https://hdl.handle.net/1..
 
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3

Structural digital twin framework: Formulation and technolo..:

Chiachío Ruano, Manuel ; Megía Cardeñoso, María ; Chiachío Ruano, Juan..
info:eu-repo/grantAgreement/EC/H2020/859957.  , 2022
Link: http://hdl.handle.net/10..
 
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4

Robust optimal sensor configuration using the value of info..:

Cantero Chinchilla, Sergio ; Chiachío Ruano, Juan ; Chiachío Ruano, Manuel
info:eu-repo/grantAgreement/EC/H2020/721455.  , 2022
Link: https://hdl.handle.net/1..
 
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5

Yield displacement charts for performance‑based seismic des..:

Hernández Montes, Enrique ; Jalón Ramírez, María Lourdes ; Chiachío Ruano, Juan.
info:eu-repo/grantAgreement/EC/H2020/821054.  , 2022
Link: https://hdl.handle.net/1..
 
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6

Intelligent health indicator construction for prognostics o..:

Moradi, Morteza ; Chiachío Ruano, Juan
info:eu-repo/grantAgreement/EC/H2020/859957.  , 2022
Link: https://hdl.handle.net/1..
 
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7

Reduction of Petri net maintenance modeling complexity via ..:

Chiachío Ruano, Manuel ; Saleh, Ali ; Chiachío Ruano, Juan
info:eu-repo/grantAgreement/EC/H2020/859957.  , 2022
Link: http://hdl.handle.net/10..
 
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8

Bayesian inverse problems: fundamentals and engineering app..:

Chiachío-Ruano, Juan - First edition . , 2021
Link: https://learning.oreilly..
 
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9

Ordering Artificial Intelligence Based Recommendations to T..:

Alonso Burgos, Sergio ; Montes Soldado, Rosa Ana ; Molina Cabrera, Daniel...
Alonso, S. [et al.]. Ordering Artificial Intelligence Based Recommendations to Tackle the SDGs with a Decision-Making Model Based on Surveys. Sustainability 2021, 13, 6038. [https://doi.org/10.3390/su13116038].  , 2021
Link: http://hdl.handle.net/10..
 
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10

Uncertainty quantification in Neural Networks by Approximat..:

Fernández Salas, Juan ; Chiachío Ruano, Manuel ; Chiachío Ruano, Juan..
info:eu-repo/grantAgreement/EC/H2020/859957.  , 2021
Link: https://hdl.handle.net/1..
 
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11

Señal ultrasónica guiada de monitorización de fatiga en pla..:

Chiachío Ruano, Manuel ; Chiachío Ruano, Juan ; Cantero Chinchilla, Sergio...
H2020 EID SAFE-PLY, Ref. 721455.  , 2020
Link: http://hdl.handle.net/10..
 
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12

OptiSens—Convex optimization of sensor and actuator placeme..:

Cantero Chinchilla, Sergio ; Beck, James L ; Chiachío Ruano, Juan..
info:eu-repo/grantAgreement/EC/H2020/721455.  , 2020
Link: http://hdl.handle.net/10..
 
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13

Plausible Petri nets as self-adaptive expert systems: A too..:

Chiachío Ruano, Manuel ; Chiachío Ruano, Juan ; Prescott, Darren.
Chiachío M, Chiachío J, Prescott D, Andrews J. Plausible Petri nets as selfadaptive expert systems: A tool for infrastructure asset monitoring. Comput Aided Civ Inf. 2019;34:281–298..  , 2019
Link: http://hdl.handle.net/10..
 
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14

A bayesian approach to fatigue damage assessment in composi..:

Chiachío Ruano, Juan
Chiachío Ruano, J. A bayesian approach to fatigue damage assessment in composite materials. Granada: Universidad de Granada, 2018. [http://hdl.handle.net/10481/51133].  , 2018
Link: http://hdl.handle.net/10..
 
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15

A knowledge-based prognostics framework for railway track g..:

Chiachío Ruano, Juan ; Chiachío Ruano, Manuel ; Prescott, Darren.
Chiachío, J., Chiachío, M., Prescott, D., & Andrews, J. (2019). A knowledge-based prognostics framework for railway track geometry degradation. Reliability Engineering & System Safety, 181, 127-141..  , 2018
Link: http://hdl.handle.net/10..
 
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