ISBN: 9780784416334 - scouring at bridge piers using artificial intelligence models: implementation and prediction (asce press) (19 resultados)

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  • Idioma: Inglés

    Editorial: American Society of Civil Engine, 2025

    0784416338 / 9780784416334

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    paperback. Condición: Fine.

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    Editorial: American Society of Civil Engineers, 2025

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  • Idioma: Inglés

    Editorial: American Society of Civil Engineers, 2025

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  • Idioma: Inglés

    Editorial: American Society of Civil Engineers, Reston, 2025

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    Paperback. Condición: new. Paperback. Scouring at Bridge Piers Using Artificial Intelligence Models: Implementation and Prediction evaluates the effectiveness of various Artificial Intelligence (AI) modelssuch as Gene-Expression Programming (GEP), Evolutionary Polynomial Regression (EPR), Model Tree (MT), and Multivariate Adaptive Regression Spline (MARS)in predicting local scour depth at bridge piers, emphasizing their physical consistency and interpretability compared to traditional methods. The author highlights the limitations of black-box AI models and aims to improve the empirical understanding of scouring data through advanced statistical analysis. Topics include Methodologies to estimate scouring at bridge piers, Effective parameters, AI models and their setting parameters, and Practical examples of AI models in scour depth prediction. Mohammad Najafzadeh has compiled this book as an innovative resource for bridge designers and professionals in field investigations and consultant engineering, such as hydraulic and transportation engineers, as well as professors and graduate students who seek to explore new potential for scouring at bridge piers using empirical equations and AI models to generate precise estimations of scour depth. Advanced AI techniquesincluding Gene-Expression Programming, Evolutionary Polynomial Regression, Model Tree, and Multivariate Adaptive Regression Splineare benchmarked for predicting local scour depth at bridge piers. The work highlights the value of physical consistency and interpretability over traditional black-box methods. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

  • Idioma: Inglés

    Editorial: John Wiley & Sons, 2025

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    Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books

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    Paperback. Condición: Brand New. 428 pages. 6.00x9.00x1.50 inches. In Stock.

  • Idioma: Inglés

    Editorial: American Society of Civil Engineers, US, 2025

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    Librería: Rarewaves.com USA, London, LONDO, Reino UnidoRarewaves.com USA

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    Paperback. Condición: New. Scouring at Bridge Piers Using Artificial Intelligence Models: Implementation and Prediction evaluates the effectiveness of various Artificial Intelligence (AI) models-such as Gene-Expression Programming (GEP), Evolutionary Polynomial Regression (EPR), Model Tree (MT), and Multivariate Adaptive Regression Spline (MARS)-in predicting local scour depth at bridge piers, emphasizing their physical consistency and interpretability compared to traditional methods. The author highlights the limitations of black-box AI models and aims to improve the empirical understanding of scouring data through advanced statistical analysis.     Topics include ·       Methodologies to estimate scouring at bridge piers, ·       Effective parameters, ·       AI models and their setting parameters, and ·       Practical examples of AI models in scour depth prediction. Mohammad Najafzadeh has compiled this book as an innovative resource for bridge designers and professionals in field investigations and consultant engineering, such as hydraulic and transportation engineers, as well as professors and graduate students who seek to explore new potential for scouring at bridge piers using empirical equations and AI models to generate precise estimations of scour depth.…

  • Idioma: Inglés

    Editorial: American Society of Civil Engineers, 2025

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    Librería: GreatBookPricesUK, Woodford Green, Reino UnidoGreatBookPricesUK

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  • Idioma: Inglés

    Editorial: American Society of Civil Engineers, 2025

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  • Idioma: Inglés

    Editorial: American Society of Civil Engineers, 2025

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    Librería: Majestic Books, Hounslow, Reino UnidoMajestic Books

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  • Idioma: Inglés

    Editorial: American Society of Civil Engineers, 2025

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  • Idioma: Inglés

    Editorial: American Society of Civil Engineers, 2025

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  • Idioma: Inglés

    Editorial: American Society of Civil Engineers, 2025

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  • Idioma: Inglés

    Editorial: American Society of Civil Engineers, 2025

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    Condición: New. 2025. paperback. . . . . . Books ship from the US and Ireland.

  • Idioma: Inglés

    Editorial: American Society of Civil Engineers, Reston, 2025

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    Paperback. Condición: new. Paperback. Scouring at Bridge Piers Using Artificial Intelligence Models: Implementation and Prediction evaluates the effectiveness of various Artificial Intelligence (AI) modelssuch as Gene-Expression Programming (GEP), Evolutionary Polynomial Regression (EPR), Model Tree (MT), and Multivariate Adaptive Regression Spline (MARS)in predicting local scour depth at bridge piers, emphasizing their physical consistency and interpretability compared to traditional methods. The author highlights the limitations of black-box AI models and aims to improve the empirical understanding of scouring data through advanced statistical analysis. Topics include Methodologies to estimate scouring at bridge piers, Effective parameters, AI models and their setting parameters, and Practical examples of AI models in scour depth prediction. Mohammad Najafzadeh has compiled this book as an innovative resource for bridge designers and professionals in field investigations and consultant engineering, such as hydraulic and transportation engineers, as well as professors and graduate students who seek to explore new potential for scouring at bridge piers using empirical equations and AI models to generate precise estimations of scour depth. Advanced AI techniquesincluding Gene-Expression Programming, Evolutionary Polynomial Regression, Model Tree, and Multivariate Adaptive Regression Splineare benchmarked for predicting local scour depth at bridge piers. The work highlights the value of physical consistency and interpretability over traditional black-box methods. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

  • Idioma: Inglés

    Editorial: American Society of Civil Engineers, US, 2025

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    Paperback. Condición: New. Scouring at Bridge Piers Using Artificial Intelligence Models: Implementation and Prediction evaluates the effectiveness of various Artificial Intelligence (AI) models-such as Gene-Expression Programming (GEP), Evolutionary Polynomial Regression (EPR), Model Tree (MT), and Multivariate Adaptive Regression Spline (MARS)-in predicting local scour depth at bridge piers, emphasizing their physical consistency and interpretability compared to traditional methods. The author highlights the limitations of black-box AI models and aims to improve the empirical understanding of scouring data through advanced statistical analysis.     Topics include ·       Methodologies to estimate scouring at bridge piers, ·       Effective parameters, ·       AI models and their setting parameters, and ·       Practical examples of AI models in scour depth prediction. Mohammad Najafzadeh has compiled this book as an innovative resource for bridge designers and professionals in field investigations and consultant engineering, such as hydraulic and transportation engineers, as well as professors and graduate students who seek to explore new potential for scouring at bridge piers using empirical equations and AI models to generate precise estimations of scour depth.…

  • Idioma: Inglés

    Editorial: American Society of Civil Engineers, Reston, 2025

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    Librería: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller

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    Paperback. Condición: new. Paperback. Scouring at Bridge Piers Using Artificial Intelligence Models: Implementation and Prediction evaluates the effectiveness of various Artificial Intelligence (AI) modelssuch as Gene-Expression Programming (GEP), Evolutionary Polynomial Regression (EPR), Model Tree (MT), and Multivariate Adaptive Regression Spline (MARS)in predicting local scour depth at bridge piers, emphasizing their physical consistency and interpretability compared to traditional methods. The author highlights the limitations of black-box AI models and aims to improve the empirical understanding of scouring data through advanced statistical analysis. Topics include Methodologies to estimate scouring at bridge piers, Effective parameters, AI models and their setting parameters, and Practical examples of AI models in scour depth prediction. Mohammad Najafzadeh has compiled this book as an innovative resource for bridge designers and professionals in field investigations and consultant engineering, such as hydraulic and transportation engineers, as well as professors and graduate students who seek to explore new potential for scouring at bridge piers using empirical equations and AI models to generate precise estimations of scour depth. Advanced AI techniquesincluding Gene-Expression Programming, Evolutionary Polynomial Regression, Model Tree, and Multivariate Adaptive Regression Splineare benchmarked for predicting local scour depth at bridge piers. The work highlights the value of physical consistency and interpretability over traditional black-box methods. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…

  • Idioma: Inglés

    Editorial: American Society Of Civil Engineers, 2025

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    Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Scouring at Bridge Piers Using Artificial Intelligence Models: Implementation and Prediction evaluates the effectiveness of various Artificial Intelligence (AI) models-such as Gene-Expression Programming (GEP), Evolutionary Polynomial Regression (EPR), Model Tree (MT), and Multivariate Adaptive Regression Spline (MARS)-in predicting local scour depth at bridge piers, emphasizing their physical consistency and interpretability compared to traditional methods. The author highlights the limitations of black-box AI models and aims to improve the empirical understanding of scouring data through advanced statistical analysis. Topics include Methodologies to estimate scouring at bridge piers, Effective parameters, AI models and their setting parameters, and Practical examples of AI models in scour depth prediction. Mohammad Najafzadeh has compiled this book as an innovative resource for bridge designers and professionals in field investigations and consultant engineering, such as hydraulic and transportation engineers, as well as professors and graduate students who seek to explore new potential for scouring at bridge piers using empirical equations and AI models to generate precise estimations of scour depth. 428 pp. Englisch.…

  • Idioma: Inglés

    Editorial: American Society Of Civil Engineers, 2025

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    Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Scouring at Bridge Piers Using Artificial Intelligence Models: Implementation and Prediction evaluates the effectiveness of various Artificial Intelligence (AI) models-such as Gene-Expression Programming (GEP), Evolutionary Polynomial Regression (EPR), Model Tree (MT), and Multivariate Adaptive Regression Spline (MARS)-in predicting local scour depth at bridge piers, emphasizing their physical consistency and interpretability compared to traditional methods. The author highlights the limitations of black-box AI models and aims to improve the empirical understanding of scouring data through advanced statistical analysis. Topics include Methodologies to estimate scouring at bridge piers, Effective parameters, AI models and their setting parameters, and Practical examples of AI models in scour depth prediction. Mohammad Najafzadeh has compiled this book as an innovative resource for bridge designers and professionals in field investigations and consultant engineering, such as hydraulic and transportation engineers, as well as professors and graduate students who seek to explore new potential for scouring at bridge piers using empirical equations and AI models to generate precise estimations of scour depth.…