Applications Of Machine Learning In Hydroclimatology

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Applications Of Machine Learning In Hydroclimatology

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Author : Roshan Srivastav
language : en
Publisher: Springer Nature
Release Date : 2024-11-04

Applications Of Machine Learning In Hydroclimatology written by Roshan Srivastav and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-04 with Mathematics categories.

Applications of Machine Learning in Hydroclimatology is a comprehensive exploration of the transformative potential of machine learning for addressing critical challenges in water resources management. The book explores how artificial intelligence can unravel the complexities of hydrological systems, providing researchers and practitioners with cutting-edge tools to model, predict, and manage these systems with greater precision and effectiveness. It thoroughly examines the modeling of hydrometeorological extremes, such as floods and droughts, which are becoming increasingly difficult to predict due to climate change. By leveraging AI-driven methods to forecast these extremes, the book offers innovative approaches that enhance predictive accuracy. It emphasizes the importance of analyzing non-stationarity and uncertainty in a rapidly evolving climate landscape, illustrating how statistical and frequency analyses can improve hydrological forecasts. Moreover, the book explores the impact of climate change on flood risks, drought occurrences, and reservoir operations, providing insights into how these phenomena affect water resource management. To provide practical solutions, the book includes case studies that showcase effective mitigation measures for water-related challenges. These examples highlight the use of machine learning techniques such as deep learning, reinforcement learning, and statistical downscaling in real-world scenarios. They demonstrate how artificial intelligence can optimize decision-making and resource management while improving our understanding of complex hydrological phenomena. By utilizing machine learning architectures tailored to hydrology, the book presents physics-guided models, data-driven techniques, and hybrid approaches that can be used to address water management issues. Ultimately, Applications of Machine Learning in Hydroclimatology empowers researchers, practitioners, and policymakers to harness machine learning for sustainable water management. It bridges the gap between advanced AI technologies and hydrological science, offering innovative solutions to tackle today's most pressing challenges in water resources.

Advanced Information Networking And Applications

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Author : Leonard Barolli
language : en
Publisher: Springer Nature
Release Date : 2025-04-07

Advanced Information Networking And Applications written by Leonard Barolli and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-07 with Computers categories.

Networks of today are going through a rapid evolution and there are many emerging areas of information networking and their applications. Heterogeneous networking supported by recent technological advances in low power wireless communications along with silicon integration of various functionalities such as sensing, communications, intelligence and actuations are emerging as a critically important disruptive computer class based on a new platform, networking structure and interface that enable novel, low-cost and high-volume applications. Several of such applications have been difficult to realize because of many interconnection problems. To fulfill their large range of applications different kinds of networks need to collaborate and wired and next generation wireless systems should be integrated in order to develop high performance computing solutions to problems arising from the complexities of these networks. This volume covers the theory, design and applications of computer networks, distributed computing and information systems. The aim of the volume “Advanced Information Networking and Applications” is to provide latest research findings, innovative research results, methods and development techniques from both theoretical and practical perspectives related to the emerging areas of information networking and applications.

Hydroclimatology Of The Great Lakes Region Of North America

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Author : Julie A. Winkler
language : en
Publisher: Frontiers Media SA
Release Date : 2022-11-14

Hydroclimatology Of The Great Lakes Region Of North America written by Julie A. Winkler 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 2022-11-14 with Science categories.

Deep Learning Concepts In Operations Research

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Author : Biswadip Basu Mallik
language : en
Publisher: CRC Press
Release Date : 2024-08-30

Deep Learning Concepts In Operations Research written by Biswadip Basu Mallik and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-30 with Computers categories.

The model-based approach for carrying out classification and identification of tasks has led to the pervading progress of the machine learning paradigm in diversified fields of technology. Deep Learning Concepts in Operations Research looks at the concepts that are the foundation of this model-based approach. Apart from the classification process, the machine learning (ML) model has become effective enough to predict future trends of any sort of phenomena. Such fields as object classification, speech recognition, and face detection have sought extensive application of artificial intelligence (AI) and ML as well. Among a variety of topics, the book examines: An overview of applications and computing devices Deep learning impacts in the field of AI Deep learning as state-of-the-art approach to AI Exploring deep learning architecture for cutting-edge AI solutions Operations research is the branch of mathematics for performing many operational tasks in other allied domains, and the book explains how the implementation of automated strategies in optimization and parameter selection can be carried out by AI and ML. Operations research has many beneficial aspects for decision making. Discussing how a proper decision depends on several factors, the book examines how AI and ML can be used to model equations and define constraints to solve problems and discover proper and valid solutions more easily. It also looks at how automation plays a significant role in minimizing human labor and thereby minimizes overall time and cost.

Hydrology And Hydroclimatology

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Author : M. Karamouz
language : en
Publisher: CRC Press
Release Date : 2012-11-27

Hydrology And Hydroclimatology written by M. Karamouz and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-11-27 with Science categories.

This book presents a systematic approach to understanding and applying the principles of hydrology and hydroclimatology, examining the interactions among different components of the water cycle. It takes a fresh look at the fundamentals and challenges in hydrologic and hydroclimatic systems as well as climate change. The author describes the applic

Visualization Techniques For Climate Change With Machine Learning And Artificial Intelligence

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Author : Ashutosh Kumar Dubey
language : en
Publisher: Elsevier
Release Date : 2022-11-11

Visualization Techniques For Climate Change With Machine Learning And Artificial Intelligence written by Ashutosh Kumar Dubey and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-11 with Science categories.

Visualization Techniques for Climate Change with Machine Learning and Artificial Intelligence covers computer-aided artificial intelligence and machine learning technologies as related to the impacts of climate change and its potential to prevent/remediate the effects. As such, different types of algorithms, mathematical relations and software models may help us to understand our current reality, predict future weather events and create new products and services to minimize human impact, chances of improving and saving lives and creating a healthier world. This book covers different types of tools for the prediction of climate change and alternative systems which can reduce the levels of threats observed by climate change scientists. Moreover, the book will help to achieve at least one of 17 sustainable development goals i.e., climate action. - Includes case studies on the application of AI and machine learning for monitoring climate change effects and management - Features applications of software and algorithms for modeling and forecasting climate change - Shows how real-time monitoring of specific factors (temperature, level of greenhouse gases, rain fall patterns, etc.) are responsible for climate change and possible mitigation efforts to achieve environmental sustainability

Connecting Mountain Hydroclimate Through The American Cordilleras

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Author : Alfonso Fernandez
language : en
Publisher: Frontiers Media SA
Release Date : 2021-05-18

Connecting Mountain Hydroclimate Through The American Cordilleras written by Alfonso Fernandez 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 2021-05-18 with Science categories.

Civil Engineering Innovations For Sustainable Communities With Net Zero Targets

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Author : Sreevalsa Kolathayar
language : en
Publisher: CRC Press
Release Date : 2024-08-27

Civil Engineering Innovations For Sustainable Communities With Net Zero Targets written by Sreevalsa Kolathayar and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-27 with Technology & Engineering categories.

This volume on civil engineering innovations for sustainable communities with net zero targets aligns with the United Nations sustainable development goals in the context of civil engineering innovations. Major topics covered include hydrological alterations under climate change, smart water management, sustainable slope stability solutions, sustainable water management and climate-smart agriculture, conservation of wetlands, influence of phase change materials on thermal properties, building information modeling (BIM) for sustainable and affordable construction, and so forth. Features: Combines concepts of civil engineering and sustainable development for future infrastructures Includes hydrological alterations under climate change impacts Covers prudent fiduciary discipline and effective cost management in the construction of buildings and critical infrastructure Discusses BIM and cost-effective sustainable construction Reviews hybrid artificial intelligence in civil infrastructure to attain SDGs #9 (industry, innovation and infrastructure) and #11 (sustainable cities and communities) This book is aimed at graduate students and researchers in civil engineering, sustainable development, risk management, GIS, and water. The Open Access version of this book, available at http://www.taylorfrancis.com, has been made available under a Creative Commons [Attribution-Non Commercial-No Derivatives (CC-BY-NC-ND)] 4.0 license.

Handbook Of Hydroinformatics

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Author : Saeid Eslamian
language : en
Publisher: Elsevier
Release Date : 2022-12-06

Handbook Of Hydroinformatics written by Saeid Eslamian and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-06 with Technology & Engineering categories.

Advanced Machine Learning Techniques includes the theoretical foundations of modern machine learning, as well as advanced methods and frameworks used in modern machine learning. Handbook of HydroInformatics, Volume II: Advanced Machine Learning Techniques presents both the art of designing good learning algorithms, as well as the science of analyzing an algorithm's computational and statistical properties and performance guarantees. The global contributors cover theoretical foundational topics such as computational and statistical convergence rates, minimax estimation, and concentration of measure as well as advanced machine learning methods, such as nonparametric density estimation, nonparametric regression, and Bayesian estimation; additionally, advanced frameworks such as privacy, causality, and stochastic learning algorithms are also included. Lastly, the volume presents Cloud and Cluster Computing, Data Fusion Techniques, Empirical Orthogonal Functions and Teleconnection, Internet of Things, Kernel-Based Modeling, Large Eddy Simulation, Patter Recognition, Uncertainty-Based Resiliency Evaluation, and Volume-Based Inverse Mode. This is an interdisciplinary book, and the audience includes postgraduates and early-career researchers interested in: Computer Science, Mathematical Science, Applied Science, Earth and Geoscience, Geography, Civil Engineering, Engineering, Water Science, Atmospheric Science, Social Science, Environment Science, Natural Resources, Chemical Engineering. - Key insights from 24 contributors in the fields of data management research, climate change and resilience, insufficient data problem, etc. - Offers applied examples and case studies in each chapter, providing the reader with real world scenarios for comparison. - Defines both the designing of good learning algorithms, as well as the science of analyzing an algorithm's computational and statistical properties and performance guarantees.

Understanding Atmospheric Rivers Using Machine Learning

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Author : Manish Kumar Goyal
language : en
Publisher: Springer Nature
Release Date : 2024-06-22

Understanding Atmospheric Rivers Using Machine Learning written by Manish Kumar Goyal and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-22 with Technology & Engineering categories.

This book delves into the characterization, impacts, drivers, and predictability of atmospheric rivers (AR). It begins with the historical background and mechanisms governing AR formation, giving insights into the global and regional perspectives of ARs, observing their varying manifestations across different geographical contexts. The book explores the key characteristics of ARs, from their frequency and duration to intensity, unraveling the intricate relationship between atmospheric rivers and precipitation. The book also focus on the intersection of ARs with large-scale climate oscillations, such as El Niño and La Niña events, the North Atlantic Oscillation (NAO), and the Pacific Decadal Oscillation (PDO). The chapters help understand how these climate phenomena influence AR behavior, offering a nuanced perspective on climate modeling and prediction. The book also covers artificial intelligence (AI) applications, from pattern recognition to prediction modeling and early warning systems. A case study on AR prediction using deep learning models exemplifies the practical applications of AI in this domain. The book culminates by underscoring the interdisciplinary nature of AR research and the synergy between atmospheric science, climatology, and artificial intelligence