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Landslides: Detection, Prediction and Monitoring
This book intends to decipher the knowledge in the advancement of understanding, detecting, predicting, and monitoring landslides. The number of massive landslides and the damages they cause has increased across the globe in recent times. It is one of the most devastating natural hazards that cause widespread damage to habitat on a local, regional, and global scale. International experts provide their experience in landslide research and practice to help stakeholders mitigate and predict potential landslides. The book comprises chapters on: Dynamics, mechanisms, and processes of landslides; Geological, geotechnical, hydrological, and geophysical modelling for landslides; Mapping and assessment of hazard, vulnerability, and risk associated with landslides; Monitoring and early warning of landslides; Application of remote sensing and GIS techniques in monitoring and assessment of landslides. The book will be of interest to researchers, practitioners, and decision-makers in adapting suitable modern techniques for landslide study.
Applications of Artificial Intelligence in Mining and Geotechnical Engineering
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,...
Proceedings of Geotechnical Challenges in Mining, Tunneling and Underground Infrastructures
This book consists of selected papers presented at the International Conference on Geotechnical Challenges in Mining, Tunneling and Underground Infrastructures (ICGMTU), held as a virtual conference on December 20, 2021. The papers represent the research work in the related fields of underground mining, ground control, mining geotechnics, geo-instrumentation, mine tunnelling, and underground structures. It focuses on the latest technology being implemented including artificial intelligence and machine learning applications to solve challenges in mining tunneling and geotechnical structure engineering. It also highlights the state-of-the-art technologies adopted by the civil and mining industry for their commercial as well as environmental benefits. The papers are presented by an international pool of academics, research scientist, and industrial experts and therefore cater to the global audience from the field of underground engineering.
Proceeding of the 3rd International Conference on Geotechnical Engineering for Disaster Mitigation and Rehabilitation 2011 Combined with the 5th International Conference on Geotechnical and Highway Engineering - Practical Applications, Challenges and Opportunities
This proceedings contains 89 papers from 25 countries and regions, including 14 keynote lectures and 17 invited lectures, presented at the Third International Conference on Geotechnical Engineering for Disaster Mitigation and Rehabilitation (3ICGEDMAR 2011) together with the Fifth International Conference on Geotechnical & Highway Engineering (5ICGHE), which was held in Semarang, Indonesia, from 18 to 20 May 2011. This is the third conference in the GEDMAR conference series. The first was held in Singapore from 12 to 13 December 2005 and the second in Nanjing, China, from 30 May to 2 June 2008. The proceedings is divided into three sections : keynote papers, invited papers and conference pap...
Machine Learning Concepts for Beginners
The book "Machine Learning Concepts for Beginners- Theory and Applications" provides the in-depth knowledge in the field of Machine Learning to graduate, post graduate and research scholars. Basically, machine learning is a field of inquiry devoted to understanding and building methods that 'learn', that is, methods that leverage data to improve performance on some set of tasks. Machine learning algorithms build a model based on sample data, known as training data, in order to make predictions or decisions without being explicitly programmed to do so.
Mastering Disruptive Technologies
About the Book: The book is divided into 4 modules which consist of 21 chapters, that narrates briefly about the top five recent emerging trends such as: Cloud Computing, Internet of Things (IoT), Blockchain, Artificial Intelligence, and Machine Learning. At the end of each module, authors have provided two Appendices. One is Job oriented short-type questions with answers, and the second one provide us different MCQs with their keys. Salient Features of the Book: Detailed Coverage on Topics like: Introduction to Cloud Computing, Cloud Architecture, Cloud Applications, Cloud Platforms, Open-Source Cloud Simulation Tools, and Mobile Cloud Computing. Expanded Coverage on Topics like: In...
Risk, Reliability and Sustainable Remediation in the Field of Civil and Environmental Engineering
Risk, Reliability and Sustainable Remediation in the Field of Civil and Environmental Engineering illustrates the concepts of risk, reliability analysis, its estimation, and the decisions leading to sustainable development in the field of civil and environmental engineering. The book provides key ideas on risks in performance failure and structural failures of all processes involved in civil and environmental systems, evaluates reliability, and discusses the implications of measurable indicators of sustainability in important aspects of multitude of civil engineering projects. It will help practitioners become familiar with tolerances in design parameters, uncertainties in the environment, a...
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