Litcius/Paper detail

Dynamic Bayesian networks for temporal prediction of chemical radioisotope levels in nuclear power plant reactors

Daniel Ramos, Pablo Ramirez-Hereza, Doroteo T. Toledano, Joaquín González-Rodríguez, Alicia Ariza-Velazquez, Daniel Solis-Tovar, Cristina Muñoz-Reja

2021Chemometrics and Intelligent Laboratory Systems17 citationsDOI

Topics & Concepts

Nuclear power plantProbabilistic logicReliability (semiconductor)Computer scienceDynamic Bayesian networkProcess (computing)Nuclear reactorBayesian networkNuclear powerThermal power stationChemical processChemical plantReliability engineeringNuclear engineeringPower (physics)Process engineeringEnvironmental scienceChemistryArtificial intelligenceEngineeringNuclear physicsPhysicsOperating systemQuantum mechanicsWaste managementOrganic chemistryEnvironmental engineeringFault Detection and Control SystemsRisk and Safety AnalysisBayesian Modeling and Causal Inference
Dynamic Bayesian networks for temporal prediction of chemical radioisotope levels in nuclear power plant reactors | Litcius