Wengang Zhang – författare

Design of Deep Braced Excavation in Urban Geotechnical Environments presents the design and calculation of deep braced excavation in urban geotechnical environments, considering the soil characteristics of spatial variability and anisotropy, as well as excavation responses of urban adjacent utilities such as pipelines, tunnels, foundation piles, and buildings. The text begins with coverage of overall stability, earth pressure and strut force, retaining wall responses, and ground movements. Numerical modeling and computer codes are also outlined in detail. Final chapters conclude with an examination of the determination of excavation responses of urban adjacent utilities and failure analysis based on several case histories.This book will be ideal for those that need the latest knowledge in both theory and practical application for deep excavation problems.

Applications of Artificial Intelligence in Mining, Geotechnical and Geoengineering provides recent advances in mining, geotechnical and geoengineering, as well as applications of artificial intelligence in these areas. It serves as the first book on applications of artificial intelligence in mining, geotechnical and geoengineering, providing an opportunity for researchers, scholars, engineers, practitioners and data scientists from all over the world to understand current developments and applications. Topics covered include slopes, open-pit mines, quarries, shafts, tunnels, caverns, underground mines, metro systems, dams and hydro-electric stations, geothermal energy, petroleum engineering, and radioactive waste disposal.

In the geotechnical and geoengineering aspects, topics of specific interest include, but are not limited to, foundation, dam, tunneling, geohazard, geoenvironmental and petroleum engineering, rock mechanics, geotechnical engineering, soil mechanics and foundation engineering, civil engineering, hydraulic engineering, petroleum engineering, engineering geology, etc.

To prevent the collapse of dangerous rock masses on steep rocky reservoir banks which can cause casualties and property loss, it is essential to design and conduct practical experiments to quantify the evolution processes of the reservoir banks and control such dangerous rock masses.

Using the Jianchuandong Dangerous Rock Mass project as a case study, this book generalizes the mechanical model of the project to show how improved equipment can be used to measure the mechanical state transition under the continuous action of axial pressure. It details a series of experiments to study the evolution of a severely steep rocky reservoir bank, which comprehensively consider the influence of hydraulic coupling, dry-wet cycles, axial pressure, and time-dependent effects. The results support a new method for determining the stability of dangerous rock masses on reservoir banks.

The book suits practitioners in hydropower engineering, engineering geology, and disaster protection.

To prevent the collapse of dangerous rock masses on steep rocky reservoir banks which can cause casualties and property loss, it is essential to design and conduct practical experiments to quantify the evolution processes of the reservoir banks and control such dangerous rock masses.

Using the Jianchuandong Dangerous Rock Mass project as a case study, this book generalizes the mechanical model of the project to show how improved equipment can be used to measure the mechanical state transition under the continuous action of axial pressure. It details a series of experiments to study the evolution of a severely steep rocky reservoir bank, which comprehensively consider the influence of hydraulic coupling, dry-wet cycles, axial pressure, and time-dependent effects. The results support a new method for determining the stability of dangerous rock masses on reservoir banks.

The book suits practitioners in hydropower engineering, engineering geology, and disaster protection.

This book brings together leading experts from around the world to explore the transformative potential of Machine Learning (ML) and the Internet of Things (IoT) in healthcare. It provides a platform for studying a future where healthcare becomes more precise, personalized, and accessible for all. The book covers recent advancements that will shape the future of healthcare and how artificial intelligence is revolutionizing disease detection, from analyzing chest X-rays for pneumonia to solving the secrets of our genes. It investigates the transformative potential of smart devices, real-time analysis of heart data, and personalized treatment plan creation. It shows how ML and IoT work and presents real-world examples of how they are leading to earlier and more accurate diagnoses and personalized treatments.

Therefore, this edited book will be an invaluable resource for researchers, healthcare professionals, data scientists, or simply someone passionate about the future of healthcare. Readers will discover the exciting possibilities that lie ahead at the crossroads of ML, IoT, and health informatics.

This book brings together leading experts from around the world to explore the transformative potential of Machine Learning (ML) and the Internet of Things (IoT) in healthcare. It provides a platform for studying a future where healthcare becomes more precise, personalized, and accessible for all. The book covers recent advancements that will shape the future of healthcare and how artificial intelligence is revolutionizing disease detection, from analyzing chest X-rays for pneumonia to solving the secrets of our genes. It investigates the transformative potential of smart devices, real-time analysis of heart data, and personalized treatment plan creation. It shows how ML and IoT work and presents real-world examples of how they are leading to earlier and more accurate diagnoses and personalized treatments.

Therefore, this edited book will be an invaluable resource for researchers, healthcare professionals, data scientists, or simply someone passionate about the future of healthcare. Readers will discover the exciting possibilities that lie ahead at the crossroads of ML, IoT, and health informatics.