Bayesian network framework probabilistic di tran thanh (8 risultati)

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  • Lingua: Inglese

    Editore: LAP LAMBERT Academic Publishing, 2022

    6205526794 / 9786205526798

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    Da: Books Puddle, New York, NY, U.S.A.Books Puddle

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    EUR 87,78

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    Condizione: New.

  • Lingua: Inglese

    Editore: LAP LAMBERT Academic Publishing, 2022

    6205526794 / 9786205526798

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    Da: preigu, Osnabrück, Germaniapreigu

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    Taschenbuch. Condizione: Neu. A Bayesian Network framework for probabilistic identification | Application for identification of model parameters in chloride ingress into concrete | Thanh Binh Tran (u. a.) | Taschenbuch | Englisch | 2022 | LAP LAMBERT Academic Publishing | EAN 9786205526798 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

  • Lingua: Inglese

    Editore: LAP LAMBERT Academic Publishing Dez 2022, 2022

    6205526794 / 9786205526798

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    Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.

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    Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Chloride ingress into concrete is one of the major causes leading to the degradation of reinforced concrete structures with important damages after 10 to 20 years. Consequently, they should be periodically inspected and repaired to ensure an optimal level of serviceability and safety. Chloride ingress involves a large number of uncertainties related to material properties and exposure conditions. However, it is difficult to obtain sufficient inspection data to characterise the mid- and long-term behaviour of this phenomenon. The main objective of this thesis is to develop a framework based on Bayesian Network updating for improving the identification of uncertainties related to material and environmental model parameters. Based on results coming from in-lab normal and accelerated tests that simulate tidal conditions, several procedures are proposed to: (1) identify input random variables from normal or natural tests; (2) determine a scale factor for accelerated tests; and (3) characterise time-dependent parameters. The results indicate that the proposed framework could be a useful tool to identify model parameters even from limited data. 196 pp. Englisch.

  • Lingua: Inglese

    Editore: LAP LAMBERT Academic Publishing, 2022

    6205526794 / 9786205526798

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    Da: Majestic Books, Hounslow, Regno UnitoMajestic Books

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    EUR 87,33

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    Quantità: 4 disponibili

    Condizione: New. Print on Demand.

  • Lingua: Inglese

    Editore: LAP LAMBERT Academic Publishing, 2022

    6205526794 / 9786205526798

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    Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios

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    EUR 88,43

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    Condizione: New. PRINT ON DEMAND.

  • Lingua: Inglese

    Editore: LAP LAMBERT Academic Publishing, 2022

    6205526794 / 9786205526798

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    Da: moluna, Greven, Germaniamoluna

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    EUR 50,51

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    Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: TRAN Thanh BinhDr. Thanh Binh TRAN is currently a lecturer of Civil Engineering in the Danang University of Technology. His research mainly focus on numerical and probabilistic modelling of the degradation processes and their interac.

  • Lingua: Inglese

    Editore: LAP LAMBERT Academic Publishing, 2022

    6205526794 / 9786205526798

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    Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH

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    EUR 92,69

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    Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Chloride ingress into concrete is one of the major causes leading to the degradation of reinforced concrete structures with important damages after 10 to 20 years. Consequently, they should be periodically inspected and repaired to ensure an optimal level of serviceability and safety. Chloride ingress involves a large number of uncertainties related to material properties and exposure conditions. However, it is difficult to obtain sufficient inspection data to characterise the mid- and long-term behaviour of this phenomenon. The main objective of this thesis is to develop a framework based on Bayesian Network updating for improving the identification of uncertainties related to material and environmental model parameters. Based on results coming from in-lab normal and accelerated tests that simulate tidal conditions, several procedures are proposed to: (1) identify input random variables from normal or natural tests; (2) determine a scale factor for accelerated tests; and (3) characterise time-dependent parameters. The results indicate that the proposed framework could be a useful tool to identify model parameters even from limited data.

  • Lingua: Inglese

    Editore: LAP LAMBERT Academic Publishing Dez 2022, 2022

    6205526794 / 9786205526798

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    Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000

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    Condizione: Nuovo

    EUR 64,90

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    Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Chloride ingress into concrete is one of the major causes leading to the degradation of reinforced concrete structures with important damages after 10 to 20 years. Consequently, they should be periodically inspected and repaired to ensure an optimal level of serviceability and safety. Chloride ingress involves a large number of uncertainties related to material properties and exposure conditions. However, it is difficult to obtain sufficient inspection data to characterise the mid- and long-term behaviour of this phenomenon. The main objective of this thesis is to develop a framework based on Bayesian Network updating for improving the identification of uncertainties related to material and environmental model parameters. Based on results coming from in-lab normal and accelerated tests that simulate tidal conditions, several procedures are proposed to: (1) identify input random variables from normal or natural tests; (2) determine a scale factor for accelerated tests; and (3) characterise time-dependent parameters. The results indicate that the proposed framework could be a useful tool to identify model parameters even from limited data.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 196 pp. Englisch.