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Novel AI Applications for Advancing Earth Sciences

Novel AI Applications for Advancing Earth Sciences PDF Author: Yadav, Sudesh
Publisher: IGI Global
ISBN:
Category : Science
Languages : en
Pages : 428

Book Description
The Earth Sciences industry faces a new challenge - the need for accurate, efficient, and reliable methods to monitor and predict geological phenomena and environmental changes. As climate change, earthquakes, and other natural disasters become more frequent and severe, the necessity for advanced tools and techniques is paramount. Traditional methods often fall short in providing the precision and speed required to address these critical issues. Geologists and earth scientists who are grappling with the urgent problem of utilizing artificial intelligence (AI) to revolutionize their field, will find the solution within the pages of Novel AI Applications for Advancing Earth Sciences. This book offers the research community concepts expanding upon the fusion of AI technology with earth sciences. By leveraging advanced AI tools, such as convolutional neural networks, support vector machines, artificial neural networks, and the potential of remote sensing satellites, this book transforms the identification of geological features, geological mapping, soil classification, and gas detection. Scientists can now predict earthquakes and assess the probability of climate change with unprecedented accuracy. Additionally, the book explains how the optimization of algorithms for specific tasks substantially reduces the time complexity of earth observations, leading to an unprecedented leap in accuracy and efficiency.

Novel AI Applications for Advancing Earth Sciences

Novel AI Applications for Advancing Earth Sciences PDF Author: Yadav, Sudesh
Publisher: IGI Global
ISBN:
Category : Science
Languages : en
Pages : 428

Book Description
The Earth Sciences industry faces a new challenge - the need for accurate, efficient, and reliable methods to monitor and predict geological phenomena and environmental changes. As climate change, earthquakes, and other natural disasters become more frequent and severe, the necessity for advanced tools and techniques is paramount. Traditional methods often fall short in providing the precision and speed required to address these critical issues. Geologists and earth scientists who are grappling with the urgent problem of utilizing artificial intelligence (AI) to revolutionize their field, will find the solution within the pages of Novel AI Applications for Advancing Earth Sciences. This book offers the research community concepts expanding upon the fusion of AI technology with earth sciences. By leveraging advanced AI tools, such as convolutional neural networks, support vector machines, artificial neural networks, and the potential of remote sensing satellites, this book transforms the identification of geological features, geological mapping, soil classification, and gas detection. Scientists can now predict earthquakes and assess the probability of climate change with unprecedented accuracy. Additionally, the book explains how the optimization of algorithms for specific tasks substantially reduces the time complexity of earth observations, leading to an unprecedented leap in accuracy and efficiency.

Deep Learning for the Earth Sciences

Deep Learning for the Earth Sciences PDF Author: Gustau Camps-Valls
Publisher: John Wiley & Sons
ISBN: 1119646162
Category : Technology & Engineering
Languages : en
Pages : 436

Book Description
DEEP LEARNING FOR THE EARTH SCIENCES Explore this insightful treatment of deep learning in the field of earth sciences, from four leading voices Deep learning is a fundamental technique in modern Artificial Intelligence and is being applied to disciplines across the scientific spectrum; earth science is no exception. Yet, the link between deep learning and Earth sciences has only recently entered academic curricula and thus has not yet proliferated. Deep Learning for the Earth Sciences delivers a unique perspective and treatment of the concepts, skills, and practices necessary to quickly become familiar with the application of deep learning techniques to the Earth sciences. The book prepares readers to be ready to use the technologies and principles described in their own research. The distinguished editors have also included resources that explain and provide new ideas and recommendations for new research especially useful to those involved in advanced research education or those seeking PhD thesis orientations. Readers will also benefit from the inclusion of: An introduction to deep learning for classification purposes, including advances in image segmentation and encoding priors, anomaly detection and target detection, and domain adaptation An exploration of learning representations and unsupervised deep learning, including deep learning image fusion, image retrieval, and matching and co-registration Practical discussions of regression, fitting, parameter retrieval, forecasting and interpolation An examination of physics-aware deep learning models, including emulation of complex codes and model parametrizations Perfect for PhD students and researchers in the fields of geosciences, image processing, remote sensing, electrical engineering and computer science, and machine learning, Deep Learning for the Earth Sciences will also earn a place in the libraries of machine learning and pattern recognition researchers, engineers, and scientists.

Large-Scale Machine Learning in the Earth Sciences

Large-Scale Machine Learning in the Earth Sciences PDF Author: Ashok N. Srivastava
Publisher: CRC Press
ISBN: 1498703887
Category : Computers
Languages : en
Pages : 208

Book Description
From the Foreword: "While large-scale machine learning and data mining have greatly impacted a range of commercial applications, their use in the field of Earth sciences is still in the early stages. This book, edited by Ashok Srivastava, Ramakrishna Nemani, and Karsten Steinhaeuser, serves as an outstanding resource for anyone interested in the opportunities and challenges for the machine learning community in analyzing these data sets to answer questions of urgent societal interest...I hope that this book will inspire more computer scientists to focus on environmental applications, and Earth scientists to seek collaborations with researchers in machine learning and data mining to advance the frontiers in Earth sciences." --Vipin Kumar, University of Minnesota Large-Scale Machine Learning in the Earth Sciences provides researchers and practitioners with a broad overview of some of the key challenges in the intersection of Earth science, computer science, statistics, and related fields. It explores a wide range of topics and provides a compilation of recent research in the application of machine learning in the field of Earth Science. Making predictions based on observational data is a theme of the book, and the book includes chapters on the use of network science to understand and discover teleconnections in extreme climate and weather events, as well as using structured estimation in high dimensions. The use of ensemble machine learning models to combine predictions of global climate models using information from spatial and temporal patterns is also explored. The second part of the book features a discussion on statistical downscaling in climate with state-of-the-art scalable machine learning, as well as an overview of methods to understand and predict the proliferation of biological species due to changes in environmental conditions. The problem of using large-scale machine learning to study the formation of tornadoes is also explored in depth. The last part of the book covers the use of deep learning algorithms to classify images that have very high resolution, as well as the unmixing of spectral signals in remote sensing images of land cover. The authors also apply long-tail distributions to geoscience resources, in the final chapter of the book.

Deep Learning for the Earth Sciences

Deep Learning for the Earth Sciences PDF Author: Gustau Camps-Valls
Publisher: John Wiley & Sons
ISBN: 1119646146
Category : Technology & Engineering
Languages : en
Pages : 436

Book Description
DEEP LEARNING FOR THE EARTH SCIENCES Explore this insightful treatment of deep learning in the field of earth sciences, from four leading voices Deep learning is a fundamental technique in modern Artificial Intelligence and is being applied to disciplines across the scientific spectrum; earth science is no exception. Yet, the link between deep learning and Earth sciences has only recently entered academic curricula and thus has not yet proliferated. Deep Learning for the Earth Sciences delivers a unique perspective and treatment of the concepts, skills, and practices necessary to quickly become familiar with the application of deep learning techniques to the Earth sciences. The book prepares readers to be ready to use the technologies and principles described in their own research. The distinguished editors have also included resources that explain and provide new ideas and recommendations for new research especially useful to those involved in advanced research education or those seeking PhD thesis orientations. Readers will also benefit from the inclusion of: An introduction to deep learning for classification purposes, including advances in image segmentation and encoding priors, anomaly detection and target detection, and domain adaptation An exploration of learning representations and unsupervised deep learning, including deep learning image fusion, image retrieval, and matching and co-registration Practical discussions of regression, fitting, parameter retrieval, forecasting and interpolation An examination of physics-aware deep learning models, including emulation of complex codes and model parametrizations Perfect for PhD students and researchers in the fields of geosciences, image processing, remote sensing, electrical engineering and computer science, and machine learning, Deep Learning for the Earth Sciences will also earn a place in the libraries of machine learning and pattern recognition researchers, engineers, and scientists.

Machine Learning and Artificial Intelligence in Geosciences

Machine Learning and Artificial Intelligence in Geosciences PDF Author:
Publisher: Academic Press
ISBN: 0128216840
Category : Science
Languages : en
Pages : 318

Book Description
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

Artificial Intelligence in Earth Science

Artificial Intelligence in Earth Science PDF Author: Ziheng Sun
Publisher: Elsevier
ISBN: 0323972160
Category : Science
Languages : en
Pages : 430

Book Description
Artificial Intelligence in Earth Science: Best Practices and Fundamental Challenges provides a comprehensive, step-by-step guide to AI workflows for solving problems in Earth Science. The book focuses on the most challenging problems in applying AI in Earth system sciences, such as training data preparation, model selection, hyperparameter tuning, model structure optimization, spatiotemporal generalization, transforming model results into products, and explaining trained models. In addition, it provides full-stack workflow tutorials to help walk readers through the whole process, regardless of previous AI experience. The book tackles the complexity of Earth system problems in AI engineering, fully guiding geoscientists who are planning to implement AI in their daily work. Provides practical, step-by-step guides for Earth Scientists who are interested in implementing AI techniques in their work Features case studies to show real-world examples of techniques described in the book Includes additional elements to help readers who are new to AI, including end-of-chapter, key concept bulleted lists that concisely cover key concepts in the chapter

Agriculture and Aquaculture Applications of Biosensors and Bioelectronics

Agriculture and Aquaculture Applications of Biosensors and Bioelectronics PDF Author: Khang, Alex
Publisher: IGI Global
ISBN:
Category : Technology & Engineering
Languages : en
Pages : 598

Book Description
In recent years, the advent of biosensors and bioelectronics has facilitated the swift and precise detection of numerous biomolecules or pathogens in animal samples, aquatic habitats, and plants. These technologies have emerged as potent assets for the agriculture and aquaculture industries. Many experts have raised the question; how might the integration of biosensors into portable devices or automated monitoring systems enable on-site and real-time detection of diverse biomolecules or pathogens? Agriculture and Aquaculture Applications of Biosensors and Bioelectronics presents the recent developments in biological recognition elements, transducer materials, and signal processing techniques for biosensors and bioelectronics used in agriculture and aquaculture applications. Sophisticated biosensors and bioelectronics operate through the immobilization of biological recognition components—such as enzymes or antibodies—on a transducer surface. This immobilization process allows for the targeted recognition and binding of biomolecules or pathogens. The resulting electrical, optical, or chemical changes triggered by the recognition event are quantifiable through various methods and are often enhanced by applications utilizing artificial intelligence (AI). The necessity for high sensitivity and selectivity, the optimization of biocompatibility and stability, and the integration of biosensors with AI-aided solutions are just some of the challenges and opportunities in developing biosensors for high-tech agriculture and aquaculture. This book targets a mixed audience of biotechnology engineers, biosensors scientists, bioelectronics researchers, high-tech agriculture analysts, Ph.D. scholars, researchers, academics, professionals, engineers, and students.

Innovations in Engineering and Food Science

Innovations in Engineering and Food Science PDF Author: Mehta, Shilpa
Publisher: IGI Global
ISBN:
Category : Technology & Engineering
Languages : en
Pages : 445

Book Description
As the global population continues to grow, the depletion of Earth's resources poses a significant challenge in ensuring food security for current and future generations. This book addresses this pressing issue by presenting innovative strategies and methods to reduce food loss, enhance production, identify alternative ingredients, and digitize the food system. It explores topics like the circular economy, cellular agriculture, artificial intelligence in food production, and novel sources of ingredients like microalgae and insects. Engineers play a pivotal role in translating ideas into tangible products and services that enhance human lives. Innovations in Engineering and Food Science is a comprehensive guide that explores the latest advancements, technologies, challenges, and solutions in the domains of engineering and food science. This book delves into the integration of cutting-edge technologies such as Artificial Intelligence (AI), Blockchain, Internet of Things (IoT), Quantum Computing, and Virtual and Augmented Reality, showcasing their potential to revolutionize the engineering landscape. With a focus on emerging technologies and practical solutions, this book serves as a valuable resource for researchers, students, academicians, and professionals in these fields.

Biosorption Processes for Heavy Metal Removal

Biosorption Processes for Heavy Metal Removal PDF Author: Saini, Pinki
Publisher: IGI Global
ISBN:
Category : Technology & Engineering
Languages : en
Pages : 390

Book Description
Persistent and non-degradable, heavy metals stand as pollutants with the potential for severe ecological repercussions when released into the environment. Municipal and industrial wastewater face a high risk of contamination by these hazardous substances, posing a formidable challenge to water treatment technologies. The imperative is clear: effective and affordable methods for effluent treatment and metal recovery are essential for meeting regulatory standards and unlocking the latent value of valuable metals within the waste. However, new methods of accomplishing this challenge are necessary for increasing the effectiveness in both cost and application Biosorption Processes for Heavy Metal Removal comprehensively explores the imperative to remove heavy metals from waste streams. It provides an insightful overview of biosorbents and biosorption technology, focusing on their underlying biosorption features. The compilation within this book comprises of a series of review articles delving into the current understanding of biosorption mechanisms and biochemistry, the efficacy of bacterial, fungal, and algal biomass, and practical considerations for biosorbent preparation and engineering. The physicochemical evaluations of biosorbents, process optimization, and factors influencing biosorption efficiency are also covered. Furthermore, the book explores biosorption applications for removing nutrients, organic pollutants, and metals in wastewater treatment across diverse contexts. Geared towards administrators, policymakers, consultants, industry professionals, academicians, scientists, researchers, and graduate and post-graduate students in environmental sciences and related fields, this book serves as their comprehensive reference.

Convergence Strategies for Green Computing and Sustainable Development

Convergence Strategies for Green Computing and Sustainable Development PDF Author: Jain, Vishal
Publisher: IGI Global
ISBN:
Category : Computers
Languages : en
Pages : 351

Book Description
Convergence Strategies for Green Computing and Sustainable Development presents a comprehensive exploration of the potential of emerging technologies, such as the Internet of Things (IoT), Artificial Intelligence (AI), fog computing, and cloud computing, to aid in fostering a sustainable future. It examines how these technologies can reduce the impact of unsustainability in societies, the environment, and natural resources, offering invaluable insights into harnessing their power for positive change. Convergence Strategies for Green Computing and Sustainable Development serves as a comprehensive strategy that holistically understands, transforms, and develops technological systems in society. This book caters to a diverse range of readers, including graduate students, researchers, working professionals seeking knowledge, and industry experts seeking information about new trends. With its recommended topics and comprehensive table of contents, readers can gain in-depth knowledge about sustainable cloud computing, artificial intelligence and machine learning for sustainable development, sustainable wireless systems and networks, and the crucial role of green IoT and Edge-AI in driving a sustainable digital transition.