Kriging in Slope Reliability Analysis
Kriging in Slope Reliability Analysis

Author: Lei-Lei Liu

Publisher: CRC Press

Published: 2024-11-25

Total Pages: 337

ISBN-13: 1040172113

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Kriging can be used to determine optimal unbiased predictions for regionalized variables and has been shown to be a powerful tool in slope reliability analysis for reliability-based design. This is the first book to systematically cover the basic theory and applications of the method in slope reliability assessment. The book gives an extensive and detailed presentation of principles and applications, introducing geostatistics and the basic theory of Kriging before addressing the challenges in the application of Kriging in slope reliability analysis. The latest advancements in Kriging application methods are introduced, which enhance computational accuracy and reduce model errors. These include optimization algorithms for spatial parameters in Kriging, adaptive modeling of spatial correlation structures, efficient sampling methods based on Monte Carlo simulation, quantitative analysis of slope failure risks, and reliability analysis methods for unreinforced and reinforced slopes based on conditional random fields. Several case studies are presented to illustrate the practical application and implementation procedures, bridging theory, and practical engineering. Kriging in Slope Reliability Analysis particularly suits consulting engineers, researchers, and postgraduate students.

Handbook of Neural Computation
Handbook of Neural Computation

Author: Pijush Samui

Publisher: Academic Press

Published: 2017-07-18

Total Pages: 660

ISBN-13: 0128113197

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Handbook of Neural Computation explores neural computation applications, ranging from conventional fields of mechanical and civil engineering, to electronics, electrical engineering and computer science. This book covers the numerous applications of artificial and deep neural networks and their uses in learning machines, including image and speech recognition, natural language processing and risk analysis. Edited by renowned authorities in this field, this work is comprised of articles from reputable industry and academic scholars and experts from around the world. Each contributor presents a specific research issue with its recent and future trends. As the demand rises in the engineering and medical industries for neural networks and other machine learning methods to solve different types of operations, such as data prediction, classification of images, analysis of big data, and intelligent decision-making, this book provides readers with the latest, cutting-edge research in one comprehensive text. - Features high-quality research articles on multivariate adaptive regression splines, the minimax probability machine, and more - Discusses machine learning techniques, including classification, clustering, regression, web mining, information retrieval and natural language processing - Covers supervised, unsupervised, reinforced, ensemble, and nature-inspired learning methods

Reliability-Based Design in Geotechnical Engineering
Reliability-Based Design in Geotechnical Engineering

Author: Kok-Kwang Phoon

Publisher: CRC Press

Published: 2008-04-21

Total Pages: 544

ISBN-13: 1482265818

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Reliability-based design is the only engineering methodology currently available which can ensure self-consistency in both physical and probabilistic terms. It is also uniquely compatible with the theoretical basis underlying other disciplines such as structural design. It is especially relevant as geotechnical design becomes subject to incre

Numerical Methods and Implementation in Geotechnical Engineering – Part 2
Numerical Methods and Implementation in Geotechnical Engineering – Part 2

Author: Y.M. Cheng

Publisher: Bentham Science Publishers

Published: 2020-04-20

Total Pages: 672

ISBN-13: 9811437408

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Numerical Methods and Implementation in Geotechnical Engineering explains several numerical methods that are used in geotechnical engineering. The second part of this reference set includes more information on the distinct element method, geotechnical optimization analysis and reliability analysis. Information about relevant additional numerical methods is also provided in each chapter with problems where applicable. The authors have also presented different computer programs associated with the materials in this book set which will be useful to students learning how to apply the models explained in the text into practical situations when designing structures in locations with specific soil and rock settings. This reference book set is a suitable textbook primer for civil engineering students as it provides a basic introduction to different numerical methods (classical and modern) in comprehensive readable volumes.

Spatial Modelling and Failure Analysis of Natural and Engineering Disasters through Data-Based Methods,volume III
Spatial Modelling and Failure Analysis of Natural and Engineering Disasters through Data-Based Methods,volume III

Author: Faming Huang

Publisher: Frontiers Media SA

Published: 2024-09-12

Total Pages: 243

ISBN-13: 2832554237

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This Research Topic is Volume III of a series. The previous volume can be found here: Spatial Modelling and Failure Analysis of Natural and Engineering Disasters through Data-based Methods - Volume II and Spatial Modelling and Failure Analysis of Natural and Engineering Disasters through Data-based Methods Natural and engineering disasters, which include landslides, rock fall, rainstorm, dam failure, floods, earthquakes, road and building disasters and wildfires, appear as results of the progressive or extreme evolution of climatic, tectonic and geomorphological processes and human engineering activities. It is significant to explore the failure mechanism and carry out spatial modeling of these engineering and natural disasters due to their serious harm to the safety of people's lives and property. The data-based methods, including advanced and successful remote sensing, geographic information systems, machine learning and numerical simulation techniques methods, are promising tools to analyze these complex disasters. Machine Learning models such as neurofuzzy logic, decision tree, artificial neural network, deep learning and evolutionary algorithms are characterized by their abilities to produce knowledge and discover hidden and unknown patterns and trends from large databases, whereas remote sensing and Geographic Information Systems appear as significant technology equipped with tools for data manipulation and advanced mathematical modeling. What is more, the numerical simulation can also be acknowledged as advanced technologies for discovering hidden failure mechanism of disasters. The main objective of this Research Topic is to provide a scientific forum for advancing the successful implementation of Machine Learning (ML) and numerical simulation techniques in operation rules, failure mechanism, spatial and time series prediction, susceptibility mapping, hazard assessment, vulnerability modeling, risk assessment and early warning of complex natural and engineering disasters.

Basic Steps in Geostatistics: The Variogram and Kriging
Basic Steps in Geostatistics: The Variogram and Kriging

Author: Margaret A. Oliver

Publisher: Springer

Published: 2015-03-30

Total Pages: 106

ISBN-13: 3319158651

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This brief will provide a bridge in succinct form between the geostatistics textbooks and the computer manuals for `push-button' practice. It is becoming increasingly important for practitioners, especially neophytes, to understand what underlies modern geostatistics and the currently available software so that they can choose sensibly and draw correct conclusions from their analysis and mapping. The brief will contain some theory, but only that needed for practitioners to understand the essential steps in analyses. It will guide readers sequentially through the stages of properly designed sampling, exploratory data analysis, variography (computing the variogram and modelling it), followed by ordinary kriging and finally mapping kriged estimates and their errors. There will be short section on trend and universal kriging. Other types of kriging will be mentioned so that readers can delve further in the substantive literature to tackle more complex tasks.

Reliability and Maintenance
Reliability and Maintenance

Author: Leo Kounis

Publisher: BoD – Books on Demand

Published: 2020-07-01

Total Pages: 206

ISBN-13: 1789239516

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Amid a plethora of challenges, technological advances in science and engineering are inadvertently affecting an increased spectrum of today’s modern life. Yet for all supplied products and services provided, robustness of processes, methods, and techniques is regarded as a major player in promoting safety. This book on systems reliability, which equally includes maintenance-related policies, presents fundamental reliability concepts that are applied in a number of industrial cases. Furthermore, to alleviate potential cost and time-specific bottlenecks, software engineering and systems engineering incorporate approximation models, also referred to as meta-processes, or surrogate models to reproduce a predefined set of problems aimed at enhancing safety, while minimizing detrimental outcomes to society and the environment.

Reliability and Statistics in Geotechnical Engineering
Reliability and Statistics in Geotechnical Engineering

Author: Gregory B. Baecher

Publisher: John Wiley & Sons

Published: 2005-08-19

Total Pages: 618

ISBN-13: 0470871253

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Risk and reliability analysis is an area of growing importance in geotechnical engineering, where many variables have to be considered. Statistics, reliability modeling and engineering judgement are employed together to develop risk and decision analyses for civil engineering systems. The resulting engineering models are used to make probabilistic predictions, which are applied to geotechnical problems. Reliability & Statistics in Geotechnical Engineering comprehensively covers the subject of risk and reliability in both practical and research terms * Includes extensive use of case studies * Presents topics not covered elsewhere--spatial variability and stochastic properties of geological materials * No comparable texts available Practicing engineers will find this an essential resource as will graduates in geotechnical engineering programmes.

Numerical Methods and Implementation in Geotechnical Engineering – Part 1
Numerical Methods and Implementation in Geotechnical Engineering – Part 1

Author: Y.M. Cheng

Publisher: Bentham Science Publishers

Published: 2020-04-01

Total Pages: 594

ISBN-13: 9811437378

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Numerical Methods and Implementation in Geotechnical Engineering explains several numerical methods that are used in geotechnical engineering. The first part of this reference set includes methods such as the finite element method, distinct element method, discontinuous deformation analysis, numerical manifold method, smoothed particle hydrodynamics method, material point method, plasticity method, limit equilibrium and limit analysis, plasticity, slope stability and foundation engineering, optimization analysis and reliability analysis. The authors have also presented different computer programs associated with the materials in this book which will be useful to students learning how to apply the models explained in the text into practical situations when designing structures in locations with specific soil and rock settings. This reference book set is a suitable textbook primer for civil engineering students as it provides a basic introduction to different numerical methods (classical and modern) in comprehensive readable volumes.

Optimization of Complex Systems: Theory, Models, Algorithms and Applications
Optimization of Complex Systems: Theory, Models, Algorithms and Applications

Author: Hoai An Le Thi

Publisher: Springer

Published: 2019-06-15

Total Pages: 1164

ISBN-13: 3030218031

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This book contains 112 papers selected from about 250 submissions to the 6th World Congress on Global Optimization (WCGO 2019) which takes place on July 8–10, 2019 at University of Lorraine, Metz, France. The book covers both theoretical and algorithmic aspects of Nonconvex Optimization, as well as its applications to modeling and solving decision problems in various domains. It is composed of 10 parts, each of them deals with either the theory and/or methods in a branch of optimization such as Continuous optimization, DC Programming and DCA, Discrete optimization & Network optimization, Multiobjective programming, Optimization under uncertainty, or models and optimization methods in a specific application area including Data science, Economics & Finance, Energy & Water management, Engineering systems, Transportation, Logistics, Resource allocation & Production management. The researchers and practitioners working in Nonconvex Optimization and several application areas can find here many inspiring ideas and useful tools & techniques for their works.