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Introduction and Applications of Machine Learning in Geotechnics offers a comprehensive exploration of machine learning methodologies and their diverse applications in geotechnical engineering. The book begins with a detailed review of machine learning methods tailored for geotechnical applications, setting the foundation for subsequent chapters. Regression models are utilized to predict shear wave velocities while optimization-based approaches are employed to determine the optimal dimensions of reinforced concrete (RC) retaining walls. The book further explores the identification of gravelly soil through optimized machine learning models and predicts stress-strain responses using data from simple shear tests.Additionally, it outlines the forecasting of liquefaction events triggered by seismic activities and estimates the uniaxial compressive strength of soil using machine learning techniques. The prediction of vertical effective stress and specific penetration resistance is examined to enhance soil characterization and geotechnical analyses. The book's authors provide valuable insights for geotechnical engineers and researchers seeking to leverage advanced computational tools for enhanced geotechnical assessments and design processes. - Provides a systematic overview of machine learning and optimization applications in geotechnical engineering- Demonstrates real-world implementations for soil classification, seismic response, and structural geotechnical interaction- Introduces interpretable and explainable AI methods for transparent engineering decision-making- Emphasizes sustainable and data-driven solutions through hybrid modeling and metaheuristic optimization

This book constitutes the refereed proceedings of the First Eurasian BIM Forum, EBF 2019, held in Istanbul, Turkey, in May 2019. BIM for project management; BIM for sustainability and performative design; BIM and facility management and infrastructural issues.

This book constitutes the refereed proceedings of the First Eurasian BIM Forum, EBF 2019, held in Istanbul, Turkey, in May 2019. The 16 full papers were carefully reviewed and selected from 44 submissions. The papers cover such topics as ​BIM adoption and implementation; BIM for project management; BIM for sustainability and performative design; BIM and facility management and infrastructural issues. 

This book constitutes the refereed proceedings of the Second Eurasian BIM Forum on Advances in Building Information Modeling, EBF 2021, held in Istanbul, Turkey, during November 11–12, 2021. The 12 full papers included in this book were carefully reviewed and selected from 22 submissions.

This book constitutes the refereed proceedings of the Second Eurasian BIM Forum on Advances in Building Information Modeling, EBF 2021, held in Istanbul, Turkey, during November 11–12, 2021.The 12 full papers included in this book were carefully reviewed and selected from 22 submissions. They were organized in topical sections as follows: BIM adoption and design process; BIM for project and facilities management; BIM education; and novel viewpoints on BIM.

3D GeoInfo aims to bring together international state-of-the-art research and facilitate the dialogue on emerging topics in the field of 3D geo-information. The conference offers an interdisciplinary forum in the fields of 3D data collection and modeling; data management for maintenance of 3D geo-information or 3D data analysis and visualization.

3D GeoInfo aims to bring together international state-of-the-art research and facilitate the dialogue on emerging topics in the field of 3D geo-information. The conference offers an interdisciplinary forum in the fields of 3D data collection and modeling; reconstruction and methods for 3D representation; data management for maintenance of 3D geo-information or 3D data analysis and visualization. The book covers the best papers from 3D GeoInfo held in Istanbul in November 2013.

This book explains how to combine and exploit sensor networks and internet-of-things (IoT) technologies and Web-service design patterns to enrich and integrate Building Information Models (BIMs). It provides approaches and software architectures for facilitating the interaction with (and between) BIMs through Web services, and for enabling and facilitating the fusion of the information residing in such models or of information acquired from IoT technologies. The proposed software architectures are presented in the form of design patterns. This information fusion will facilitate many novel application fields ranging from emergency response, to urban monitoring and surveillance, and to smart buildings.The book consists of 8 chapters. The first 2 chapters focus on the basics of BIMs, while chapter 3 presents fundamental service-oriented architecture patterns for complex information models. Subsequently, chapters 4 and 5 elaborate on the hardware and software side of IoT, with aspecial focus on their use for BIMs. Chapter 6 provides advanced SOA patterns for BIMs, while chapter 7 details patterns for IoT, and for BIM and IoT information fusion. Lastly, chapter 8 summarizes the work and provides an outlook on promising future developments. Overall, the book will be beneficial for researchers and developers in the fields of building information models, IoT applications, and systems integration.