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Broadening The Use Of Machine Learning In Hydrology


Broadening The Use Of Machine Learning In Hydrology
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Broadening The Use Of Machine Learning In Hydrology


Broadening The Use Of Machine Learning In Hydrology
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Author : Chaopeng Shen
language : en
Publisher: Frontiers Media SA
Release Date : 2021-07-08

Broadening The Use Of Machine Learning In Hydrology written by Chaopeng Shen 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 2021-07-08 with Science categories.




Handbook Of Hydroinformatics


Handbook Of Hydroinformatics
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Author : Saeid Eslamian
language : en
Publisher: Elsevier
Release Date : 2022-11-30

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 2022-11-30 with Technology & Engineering categories.


Classic Soft-Computing Techniques is the first volume of the three, in the Handbook of HydroInformatics series. Through this comprehensive, 34-chapters work, the contributors explore the difference between traditional computing, also known as hard computing, and soft computing, which is based on the importance given to issues like precision, certainty and rigor. The chapters go on to define fundamentally classic soft-computing techniques such as Artificial Neural Network, Fuzzy Logic, Genetic Algorithm, Supporting Vector Machine, Ant-Colony Based Simulation, Bat Algorithm, Decision Tree Algorithm, Firefly Algorithm, Fish Habitat Analysis, Game Theory, Hybrid Cuckoo–Harmony Search Algorithm, Honey-Bee Mating Optimization, Imperialist Competitive Algorithm, Relevance Vector Machine, etc. It is a fully comprehensive handbook providing all the information needed around classic soft-computing techniques. This volume is a true interdisciplinary work, 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, and Chemical Engineering. - Key insights from global 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. - Introduces classic soft-computing techniques, necessary for a range of disciplines.



Advancements In Machine Learning And Natural Language Processing Innovations And Applications


Advancements In Machine Learning And Natural Language Processing Innovations And Applications
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Author : Lamia Hadrich Belguith
language : en
Publisher: Springer Nature
Release Date : 2025-03-27

Advancements In Machine Learning And Natural Language Processing Innovations And Applications written by Lamia Hadrich Belguith and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-27 with Computers categories.


This book discovers groundbreaking advancements in artificial intelligence with innovative solutions for real-world challenges. This book showcases state-of-the-art methodologies like deep learning and transfer learning to tackle sentiment analysis, fake news detection, and multi-dialectal named entity recognition, with a special focus on Arabic language technologies. Bridging the gap between research and practice, it highlights topics such as knowledge extraction, AI ethics, and the societal impacts of big data. Targeted at researchers, educators, and professionals, it serves as a vital guide for beginners and a comprehensive reference for experts seeking to stay ahead in the rapidly evolving field of AI.



Advances In Hydroinformatics Simhydro 2023 Volume 2


Advances In Hydroinformatics Simhydro 2023 Volume 2
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Author : Philippe Gourbesville
language : en
Publisher: Springer Nature
Release Date : 2024-09-17

Advances In Hydroinformatics Simhydro 2023 Volume 2 written by Philippe Gourbesville and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-17 with Science categories.


This book includes a collection of extended papers based on presentations given during the SimHydro 2023 conference, held in EDF Lab Chatou, France, with the support of Société Hydrotechnique de France (SHF), the Association Française de Mécanique (AFM), the Environmental and Water Resources Institute (EWRI), and the International Association for Hydro-Environment Engineering and Research (IAHR). SimHydro conferences, since 2010, have created a regular forum where major actors of the hydroinformatics domain and stakeholders meet, share, and debate about needs, innovations, and implementations of models and their inputs for decision making. For this new edition, the general theme of the conference is focused on “New modelling paradigms for water issues”. The papers address some of the key challenges faced by the water modelling community regarding processes to simulate such as water services, extreme events (floods, droughts, etc.), and hydrological cycle at catchment scale and to assess the added value of emerging concepts and methods such as Artificial Intelligence (AI) and Digital Twins that are gaining interests. It addresses the interests of practitioners, stakeholders, researchers, and engineers active in this field. This book represents Volume 2 of a two-volume book series.



Machine Learning For Civil And Environmental Engineers


Machine Learning For Civil And Environmental Engineers
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Author : M. Z. Naser
language : en
Publisher: John Wiley & Sons
Release Date : 2023-07-17

Machine Learning For Civil And Environmental Engineers written by M. Z. Naser 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 2023-07-17 with Technology & Engineering categories.


Accessible and practical framework for machine learning applications and solutions for civil and environmental engineers This textbook introduces engineers and engineering students to the applications of artificial intelligence (AI), machine learning (ML), and machine intelligence (MI) in relation to civil and environmental engineering projects and problems, presenting state-of-the-art methodologies and techniques to develop and implement algorithms in the engineering domain. Through real-world projects like analysis and design of structural members, optimizing concrete mixtures for site applications, examining concrete cracking via computer vision, evaluating the response of bridges to hazards, and predicating water quality and energy expenditure in buildings, this textbook offers readers in-depth case studies with solved problems that are commonly faced by civil and environmental engineers. The approaches presented range from simplified to advanced methods, incorporating coding-based and coding-free techniques. Professional engineers and engineering students will find value in the step-by-step examples that are accompanied by sample databases and codes for readers to practice with. Written by a highly qualified professional with significant experience in the field, Machine Learning includes valuable information on: The current state of machine learning and causality in civil and environmental engineering as viewed through a scientometrics analysis, plus a historical perspective Supervised vs. unsupervised learning for regression, classification, and clustering problems Explainable and causal methods for practical engineering problems Database development, outlining how an engineer can effectively collect and verify appropriate data to be used in machine intelligence analysis A framework for machine learning adoption and application, covering key questions commonly faced by practitioners This textbook is a must-have reference for undergraduate/graduate students to learn concepts on the use of machine learning, for scientists/researchers to learn how to integrate machine learning into civil and environmental engineering, and for design/engineering professionals as a reference guide for undertaking MI design, simulation, and optimization for infrastructure.



Computational Methods For Time Series Analyses In Earth Sciences


Computational Methods For Time Series Analyses In Earth Sciences
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Author : Silvio José Gumiere
language : en
Publisher: Elsevier
Release Date : 2025-06-27

Computational Methods For Time Series Analyses In Earth Sciences written by Silvio José Gumiere and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-27 with Science categories.


Computational Methods for Time-Series Analyses in Earth Sciences bridges the gap between theoretical knowledge and practical application, offering a deep dive into the utilization of R programming for managing, analyzing, and forecasting time-series data within the realm of Earth sciences. It systematically unfolds the layers of data manipulation, graphical representation, and sampling to prepare the reader for complex analyses and predictive modeling from the basics of signal processing to the nuances of machine learning. It presents cutting-edge techniques, such as neural networks, kernel-based methods, and evolutionary algorithms, specifically tailored to tackle challenges, and provides practical case studies to aid readers with utilizing the techniques covered.Computational Methods for Time-Series Analyses in Earth Sciences is a valuable resource for scientists, researchers, and students delving into the intricacies of Earth's environmental patterns and cycles through the lens of computational analysis and guides readers through various computational approaches to deciphering spatial and temporal data. - Focuses on the use of R for time-series analysis and the application of these methods directly to Earth and environmental datasets - Integrates Machine Learning techniques, enabling readers to explore advanced computational methods for forecasting and modeling - Includes case studies with real-world applications, providing readers with examples on how to translate computational skills into tangible outcomes



Food And Nutrition Security In The Kingdom Of Saudi Arabia Vol 2


Food And Nutrition Security In The Kingdom Of Saudi Arabia Vol 2
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Author : Adam E. Ahmed
language : en
Publisher: Springer Nature
Release Date : 2024-01-01

Food And Nutrition Security In The Kingdom Of Saudi Arabia Vol 2 written by Adam E. Ahmed and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-01 with Technology & Engineering categories.


Food and nutrition security is a major concern for Saudi Arabia and the surrounding regions due to the range of challenges they face. These challenges include limited agricultural resources, low self-sufficiency in key food staples, climate change, and high levels of food loss and waste. This book aims to evaluate and analyze the current situation and future prospects of food and nutrition security in Saudi Arabia. Additionally, it seeks to analyze and assess the roles and functions of various institutions related to food security, providing a deeper understanding of the complex problems associated with it. Furthermore, this book aligns with Kingdom Vision 2030, which includes a set of strategies and programs focused on agriculture, food, and water security. It also aligns with the institutional identity of King Faisal University's "Food Security and Environmental Sustainability". The book consists of four volumes. Volume 2 is entitled "Macroeconomic Policy Implications on Food and Nutrition Security". It covers various areas, including food price, loss and waste, processing, finance, trade, investment, quality and safety, consumption patterns, climate change, early warning systems, nutrition institutions, oil revenue, and the significance of date palm and Hassawi rice, genetically modified food, and edible insects in ensuring food and nutritional security. This book is highly significant for professionals, researchers, policymakers, and entrepreneurs involved in food and nutrition security in Saudi Arabia, the Gulf Cooperation Council, and various national and international organizations. It offers a comprehensive analysis of the obstacles and possibilities in ensuring food and nutrition security, as well as presenting practical approaches to address these issues. Additionally, graduate students studying in fields related to food and nutrition security will benefit from this book.



Forest Water Interactions


Forest Water Interactions
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Author : Delphis F. Levia
language : en
Publisher: Springer
Release Date : 2020-02-06

Forest Water Interactions written by Delphis F. Levia and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-02-06 with Science categories.


The United Nations has declared 2018-2028 as the International Decade for Action on Water for Sustainable Development. This is a timely designation. In an increasingly thirsty world, the subject of forest-water interactions is of critical importance to the achievement of sustainability goals. The central underlying tenet of this book is that the hydrologic community can conduct better science and make a more meaningful impact to the world’s water crisis if scientists are: (1) better equipped to utilize new methods and harness big data from either or both high-frequency sensors and long-term research watersheds; and (2) aware of new developments in our process-based understanding of the hydrological cycle in both natural and urban settings. Accordingly, this forward-looking book delves into forest-water interactions from multiple methodological, statistical, and process-based perspectives (with some chapters featuring data sets and open-source R code), concluding with a chapter on future forest hydrology under global change. Thus, this book describes the opportunities of convergence in high-frequency sensing, big data, and open source software to catalyze more comprehensive understanding of forest-water interactions. The book will be of interest to researchers, graduate students, and advanced undergraduates in an array of disciplines, including hydrology, forestry, ecology, botany, and environmental engineering.



Artificial Neural Networks In Hydrology


Artificial Neural Networks In Hydrology
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Author : R.S. Govindaraju
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-09

Artificial Neural Networks In Hydrology written by R.S. Govindaraju and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-09 with Science categories.


R. S. GOVINDARAJU and ARAMACHANDRA RAO School of Civil Engineering Purdue University West Lafayette, IN. , USA Background and Motivation The basic notion of artificial neural networks (ANNs), as we understand them today, was perhaps first formalized by McCulloch and Pitts (1943) in their model of an artificial neuron. Research in this field remained somewhat dormant in the early years, perhaps because of the limited capabilities of this method and because there was no clear indication of its potential uses. However, interest in this area picked up momentum in a dramatic fashion with the works of Hopfield (1982) and Rumelhart et al. (1986). Not only did these studies place artificial neural networks on a firmer mathematical footing, but also opened the dOOf to a host of potential applications for this computational tool. Consequently, neural network computing has progressed rapidly along all fronts: theoretical development of different learning algorithms, computing capabilities, and applications to diverse areas from neurophysiology to the stock market. . Initial studies on artificial neural networks were prompted by adesire to have computers mimic human learning. As a result, the jargon associated with the technical literature on this subject is replete with expressions such as excitation and inhibition of neurons, strength of synaptic connections, learning rates, training, and network experience. ANNs have also been referred to as neurocomputers by people who want to preserve this analogy.



Machine Learning Methods In The Environmental Sciences


Machine Learning Methods In The Environmental Sciences
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Author : William W. Hsieh
language : en
Publisher: Cambridge University Press
Release Date : 2009-07-30

Machine Learning Methods In The Environmental Sciences written by William W. Hsieh and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-07-30 with Computers categories.


A graduate textbook that provides a unified treatment of machine learning methods and their applications in the environmental sciences.