Applications Of Machine Learning In Volcanology
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Applications Of Machine Learning In Volcanology
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Author : Bellina Di Lieto
language : en
Publisher: Frontiers Media SA
Release Date : 2025-04-29
Applications Of Machine Learning In Volcanology written by Bellina Di Lieto and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-29 with Science categories.
The characterization of volcano state is not a simple task due the complexity of physics processes underway. Understanding their evolution prior to and during eruptions is a critical point for identifying transitions in volcanic state. Permanent monitoring networks are developed for such a purpose. With the increase of the number of monitoring sites, the amount of available continuous data coming from different sources (infrasonic, seismic, GPS, geochemical, etc.) has increased exponentially and extracting the huge amount of information this data brings, represents a non-trivial task for researchers, who are always more often looking at the potentiality of computer algorithms to find correlations among them. Recent developments in the field of Machine Learning (ML) have proven to be very useful and efficient for automatic discrimination, decision, prediction, clustering and information extraction in many fields, including volcanology. In recent times, Deep Learning has seen rapid growth in its popularity along with other supervised strategies, such as Support Vectors Machines and Recurrent neural networks (RNN), which have consistently been applied with success to broader and broader sets of applications and fields. However, supervised machine learning requires labels for training, and obtaining these labels for large volumes of seismic and volcanic data is a very demanding and challenging task. Therefore, semi-supervised and unsupervised methods, such as Self-organized Maps, have been applied with success, to extract relevant information from huge amounts of unlabelled data. In seismic and deformative data processing, these techniques are used for waveform inversion, automatic picking of first arrivals, and interpretation of peculiar characteristics of transients. ML is helpful in the discrimination of magmatic complexes, in distinguishing tectonic settings of volcanic rocks, in the evaluation of correlations between volcanic signals and the chemico-physical composition of erupted materials. Other applications of ML in volcanology include the analysis and classification of geological, geochemical and petrological “static” data to infer for example, the possible source and mechanism of observed deposits, the analysis of satellite imagery to quickly classify vast regions difficult to investigate on the ground or, again, to detect changes that could indicate an unrest. The results obtained with the help of these algorithms would otherwise represent for researchers’ tasks hard to be solved with the usual standard methodologies.
Intelligent Methods With Applications In Volcanology And Seismology
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Author : Alireza Hajian
language : en
Publisher: Springer Nature
Release Date : 2023-03-01
Intelligent Methods With Applications In Volcanology And Seismology written by Alireza Hajian and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-01 with Science categories.
This book presents intelligent methods like neural, neuro-fuzzy, machine learning, deep learning and metaheuristic methods and their applications in both volcanology and seismology. The complex system of volcanoes and also earthquakes is a big challenge to identify their behavior using available models, which motivates scientists to apply non-model based methods. As there are lots of seismology and volcanology data sets, i.e., the local and global networks, one solution is using intelligent methods in which data-based algorithms are used.
Chapter Machine Learning In Volcanology A Review
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Author : Roberto Carniel
language : en
Publisher:
Release Date : 2020
Chapter Machine Learning In Volcanology A Review written by Roberto Carniel and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with categories.
A volcano is a complex system, and the characterization of its state at any given time is not an easy task. Monitoring data can be used to estimate the probability of an unrest and/or an eruption episode. These can include seismic, magnetic, electromagnetic, deformation, infrasonic, thermal, geochemical data or, in an ideal situation, a combination of them. Merging data of different origins is a non-trivial task, and often even extracting few relevant and information-rich parameters from a homogeneous time series is already challenging. The key to the characterization of volcanic regimes is in fact a process of data reduction that should produce a relatively small vector of features. The next step is the interpretation of the resulting features, through the recognition of similar vectors and for example, their association to a given state of the volcano. This can lead in turn to highlight possible precursors of unrests and eruptions. This final step can benefit from the application of machine learning techniques, that are able to process big data in an efficient way. Other applications of machine learning in volcanology include the analysis and classification of geological, geochemical and petrological “static” data to infer for example, the possible source and mechanism of observed deposits, the analysis of satellite imagery to quickly classify vast regions difficult to investigate on the ground or, again, to detect changes that could indicate an unrest. Moreover, the use of machine learning is gaining importance in other areas of volcanology, not only for monitoring purposes but for differentiating particular geochemical patterns, stratigraphic issues, differentiating morphological patterns of volcanic edifices, or to assess spatial distribution of volcanoes. Machine learning is helpful in the discrimination of magmatic complexes, in distinguishing tectonic settings of volcanic rocks, in the evaluation of correlations of volcanic units, being particularly helpful in tephrochronology, etc. In this chapter we will review the relevant methods and results published in the last decades using machine learning in volcanology, both with respect to the choice of the optimal feature vectors and to their subsequent classification, taking into account both the unsupervised and the supervised approaches.
Muography
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Author : László Oláh
language : en
Publisher: John Wiley & Sons
Release Date : 2022-01-25
Muography written by László Oláh and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-25 with Science categories.
A technique for visualizing Earth's subsurface at high resolution Hidden out of sight in Earth’s subsurface are a range of geophysical structures, processes, and material movements. Muography is a passive and non-destructive remote sensing technique that visualizes the internal structure of solid geological structures at high resolution, similar in process to X-ray radiography of human bodies. Muography: Exploring Earth's Subsurface with Elementary Particles explores the application of this imaging technique in the geosciences and how it can complement conventional geophysical observations. Volume highlights include: Principles of muography and pioneering works in the field Different approaches for muographic image processing Observing volcanic structures and activity with muography Using muography for geophysical exploration and mining engineering Potential environmental applications of muography Latest technological developments in muography The American Geophysical Union promotes discovery in Earth and space science for the benefit of humanity. Its publications disseminate scientific knowledge and provide resources for researchers, students, and professionals.
Towards Improved Forecasting Of Volcanic Eruptions
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Author : Corentin Caudron
language : en
Publisher: Frontiers Media SA
Release Date : 2020-04-01
Towards Improved Forecasting Of Volcanic Eruptions written by Corentin Caudron and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-01 with categories.
Prospects Of Artificial Intelligence In The Environment
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Author : Ajitanshu Vedrtnam
language : en
Publisher: Springer Nature
Release Date : 2025-07-19
Prospects Of Artificial Intelligence In The Environment written by Ajitanshu Vedrtnam and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-19 with Technology & Engineering categories.
This book gives readers insight into the state-of-the-art use of artificial intelligence for the environment. It encompasses most of the significant facets of current breakthroughs in the fields of conceptions, methodologies, resources, and leading artificial intelligence solutions for the environment. This book presents research at the forefront on applications of artificial intelligence in combating climate change, natural hazards, and textile dyeing pollution (water pollution), for forecasting, assessing air quality trends, and air pollution monitoring. It explains how machine learning can prove to be an efficient technique to forecast the consumption of energy and how AI can be effective for renewable energy systems. Research in this book widens its scope to present the problems, opportunities, and directives for the application of AI systems in engine exhaust prediction. One of the new and interesting things explored is to provide and predict the rate of decay of human lung tissue (due to Particulate Matter exposure) with the help of AI in this book. Likewise, the book opens its scope to various environmental problems and focuses on giving the best solutions with an application of artificial intelligence; this feature makes this book an indispensable guide for environmental scientists and AI researchers of all levels. The book is written comprehensively so that engineering professionals, programmers, environmentalists, graduates, postgraduates, and researchers from beginning/intermediate level to advance level can be enlightened.
Next Generation Wireless Networks Meet Advanced Machine Learning Applications
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Author : Comşa, Ioan-Sorin
language : en
Publisher: IGI Global
Release Date : 2019-01-25
Next Generation Wireless Networks Meet Advanced Machine Learning Applications written by Comşa, Ioan-Sorin and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-25 with Technology & Engineering categories.
The ever-evolving wireless technology industry is demanding new technologies and standards to ensure a higher quality of experience for global end-users. This developing challenge has enabled researchers to identify the present trend of machine learning as a possible solution, but will it meet business velocity demand? Next-Generation Wireless Networks Meet Advanced Machine Learning Applications is a pivotal reference source that provides emerging trends and insights into various technologies of next-generation wireless networks to enable the dynamic optimization of system configuration and applications within the fields of wireless networks, broadband networks, and wireless communication. Featuring coverage on a broad range of topics such as machine learning, hybrid network environments, wireless communications, and the internet of things; this publication is ideally designed for industry experts, researchers, students, academicians, and practitioners seeking current research on various technologies of next-generation wireless networks.
Machine Learning And Artificial Intelligence In Geosciences
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Author :
language : en
Publisher: Academic Press
Release Date : 2020-09-22
Machine Learning And Artificial Intelligence In Geosciences written by and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-22 with Science categories.
Advances in Geophysics, Volume 61 - Machine Learning and Artificial Intelligence in Geosciences, the latest release in this highly-respected publication in the field of geophysics, contains new chapters on a variety of topics, including a historical review on the development of machine learning, machine learning to investigate fault rupture on various scales, a review on machine learning techniques to describe fractured media, signal augmentation to improve the generalization of deep neural networks, deep generator priors for Bayesian seismic inversion, as well as a review on homogenization for seismology, and more. - Provides high-level reviews of the latest innovations in geophysics - Written by recognized experts in the field - Presents an essential publication for researchers in all fields of geophysics
The Volcano Equation Breaking Down Volcanology
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Author : Lexa N. Palmer
language : en
Publisher: Book Lovers HQ
Release Date : 2024-12-04
The Volcano Equation Breaking Down Volcanology written by Lexa N. Palmer and has been published by Book Lovers HQ this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-04 with Science categories.
The Volcano Equation: Breaking Down Volcanology is an immersive exploration into the mesmerizing world of volcanic studies. This comprehensive analysis combines cutting-edge research, advanced monitoring techniques, and fundamental geological principles to explain how these powerful natural phenomena shape our planet. This book demystifies the complex processes that drive volcanic activity, from the microscopic analysis of crystal formation to the grand scale of tectonic plate movements. Expert insights reveal how modern technology—including artificial intelligence, satellite monitoring, and quantum sensors—is revolutionizing our understanding of magma dynamics and eruption predictions. Inside these pages, you'll discover the intricate relationships between seismic activity, gas emissions, and ground deformation that signal impending eruptions. The book explores how volcanoes interact with each other across vast distances through subtle stress changes in Earth's crust, challenging previous assumptions about isolated volcanic systems. What you will find in this book: In-depth analysis of magma chamber dynamics and crystal formation processes Detailed explanations of monitoring techniques using cutting-edge technology Real-world examples of volcanic hazard assessment and risk mitigation Historical perspectives on major eruptions and their global impacts Current research on the effects of climate change on volcanic activity Practical insights into living and adapting to life in volcanic regions Advanced concepts in geochemistry and volcanic rock formation Latest developments in eruption prediction and early warning systems Whether you're a geology student, Earth science professional, or simply fascinated by these geological giants, The Volcano Equation offers clear explanations of complex volcanic processes. The book bridges the gap between traditional geological studies and modern technological approaches, providing a fresh perspective on volcanology. This authoritative resource combines scientific rigor with accessible language, making it valuable for academic study and professional reference. Readers gain insights into one of nature's most powerful forces by understanding the intricate "equation" of variables that influence volcanic behavior. Join the journey into Earth's fiery depths and discover how the science of volcanology continues to evolve, protecting communities and advancing our knowledge of planetary processes.
Nature Inspired Computation And Machine Learning
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Author : Alexander Gelbukh
language : en
Publisher: Springer
Release Date : 2014-11-05
Nature Inspired Computation And Machine Learning written by Alexander Gelbukh and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-11-05 with Computers categories.
The two-volume set LNAI 8856 and LNAI 8857 constitutes the proceedings of the 13th Mexican International Conference on Artificial Intelligence, MICAI 2014, held in Tuxtla, Mexico, in November 2014. The total of 87 papers plus 1 invited talk presented in these proceedings were carefully reviewed and selected from 348 submissions. The first volume deals with advances in human-inspired computing and its applications. It contains 44 papers structured into seven sections: natural language processing, natural language processing applications, opinion mining, sentiment analysis, and social network applications, computer vision, image processing, logic, reasoning, and multi-agent systems, and intelligent tutoring systems. The second volume deals with advances in nature-inspired computation and machine learning and contains also 44 papers structured into eight sections: genetic and evolutionary algorithms, neural networks, machine learning, machine learning applications to audio and text, data mining, fuzzy logic, robotics, planning, and scheduling, and biomedical applications.