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Soft Computing and Machine Learning in Dam Engineering

"Soft Computing and Machine Learning in Dam Engineering" is a comprehensive, edited Special Issue that explores the latest advances in the application of soft computing and machine learning techniques to dam engineering. This reprint covers a range of topics, including dam design, construc...

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Bibliographic Details
Main Author: Hariri-Ardebili, M. Amin
Other Authors: Salazar, Fernando, Pourkamali-Anaraki, Farhad, Mazzà, Guido
Format: eBook
Language:English
Published: Basel MDPI - Multidisciplinary Digital Publishing Institute 2023
Subjects:
Machine Learning
Polynomial Chaos Expansion
Dam Safety
Ice Loads
Feasibility Design
Random Forest
Finite Element
Support Vector Machines
Probabilistic Analysis
Automl
N/a
Moving Average Of The Residuals
Moving Standard Deviation Of The Residuals
Model Validation
One-class Classification
Tensile And Compressive Damage
Monitoring
Machine Learning Methods
Parameter Uncertainty
Uncertainty
Multilayer Perceptron Neural Network Model
History Of Engineering & Technology / Bicssc
Safety Assessment
Deep Neural Networks
Design Variable
Gravity Dams
Non-linear Structural Analysis
Technology: General Issues / Bicssc
Structural Behaviour
Concrete Damage Model
Arch Dams
Risk-informed Design
Vibration Analysis
Threshold Definition
Endurance Time Analysis
Roller Compacted Concrete (rcc)
Cascadia Subduction Zone (csz)
Rockfill Dams
Sensitivity Analysis
Concrete Dams
Back-calculation
Structural Health Monitoring
Non-linear Seismic Analysis
Variance-based Sensitivity Analysis
Random Fields
Anomaly Detection
Dbscan
Sample Optimization
Surrogate
Seismic Safety
Concrete Dam
Dams
Online Access:
Collection: Directory of Open Access Books - Collection details see MPG.ReNa
Description
Summary:"Soft Computing and Machine Learning in Dam Engineering" is a comprehensive, edited Special Issue that explores the latest advances in the application of soft computing and machine learning techniques to dam engineering. This reprint covers a range of topics, including dam design, construction, monitoring, and maintenance, and provides readers with a deep understanding of the theoretical foundations and practical applications of these techniques.Featuring contributions from leading experts in the field, the reprint presents a collection of 11 papers that offer insights into state-of-the-art approaches in dam engineering. The chapters cover topics such as fuzzy logic, genetic algorithms, artificial neural networks, and support vector machines, and provide practical examples of how these techniques can be applied to solve real-world dam engineering problems.Whether you are a researcher, engineer, or student in the field of dam engineering, "Soft Computing and Machine Learning in Dam Engineering" provides a valuable resource for staying up-to-date with the latest techniques and approaches in the field.
Item Description:Creative Commons (cc), https://creativecommons.org/licenses/by/4.0/
Physical Description:1 electronic resource (260 p.)
ISBN:books978-3-0365-7578-0
9783036575780
9783036575797

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