9780784416334 - scouring at bridge piers using artificial intelligence models: implementation and prediction di najafzadeh, mohammad (13 risultati)
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Da: ThriftBooks-Dallas, Dallas, TX, U.S.A.ThriftBooks-Dallas
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Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books
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Da: Rarewaves.com USA, London, LONDO, Regno UnitoRarewaves.com USA
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Paperback. Condizione: 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 Regres…sion 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.
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Da: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail
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Paperback. Condizione: 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 Adapt…ive 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.
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Da: Majestic Books, Hounslow, Regno UnitoMajestic Books
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Da: Kennys Bookstore, Olney, MD, U.S.A.Kennys Bookstore
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Condizione: New. 2025. paperback. . . . . . Books ship from the US and Ireland.
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Da: CitiRetail, Stevenage, Regno UnitoCitiRetail
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Paperback. Condizione: 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 Adapt…ive 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.
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Da: Rarewaves.com UK, London, Regno UnitoRarewaves.com UK
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
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Paperback. Condizione: 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 Regres…sion 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.
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Da: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 285,94
EUR 31,86 spedizioneSpedito da Australia a U.S.A.Quantità: 1 disponibili
Paperback. Condizione: 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 Adapt…ive 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.
