Download or read book Artificial Intelligence Methods in the Environmental Sciences written by Sue Ellen Haupt and published by Springer Science & Business Media. This book was released on 2008-11-28 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: How can environmental scientists and engineers use the increasing amount of available data to enhance our understanding of planet Earth, its systems and processes? This book describes various potential approaches based on artificial intelligence (AI) techniques, including neural networks, decision trees, genetic algorithms and fuzzy logic. Part I contains a series of tutorials describing the methods and the important considerations in applying them. In Part II, many practical examples illustrate the power of these techniques on actual environmental problems. International experts bring to life ways to apply AI to problems in the environmental sciences. While one culture entwines ideas with a thread, another links them with a red line. Thus, a “red thread“ ties the book together, weaving a tapestry that pictures the ‘natural’ data-driven AI methods in the light of the more traditional modeling techniques, and demonstrating the power of these data-based methods.

Download or read book Artificial Intelligence Methods in the Environmental Sciences written by Sue Ellen Haupt and published by Springer. This book was released on 2009-08-29 with total page 424 pages. Available in PDF, EPUB and Kindle. Book excerpt: How can environmental scientists and engineers use the increasing amount of available data to enhance our understanding of planet Earth, its systems and processes? This book describes various potential approaches based on artificial intelligence (AI) techniques, including neural networks, decision trees, genetic algorithms and fuzzy logic. Part I contains a series of tutorials describing the methods and the important considerations in applying them. In Part II, many practical examples illustrate the power of these techniques on actual environmental problems. International experts bring to life ways to apply AI to problems in the environmental sciences. While one culture entwines ideas with a thread, another links them with a red line. Thus, a “red thread“ ties the book together, weaving a tapestry that pictures the ‘natural’ data-driven AI methods in the light of the more traditional modeling techniques, and demonstrating the power of these data-based methods.

Download or read book Machine Learning Methods in the Environmental Sciences written by William W. Hsieh and published by Cambridge University Press. This book was released on 2009-07-30 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: A graduate textbook that provides a unified treatment of machine learning methods and their applications in the environmental sciences.

Download or read book Computational Intelligence Techniques in Earth and Environmental Sciences written by Tanvir Islam and published by Springer Science & Business Media. This book was released on 2014-02-14 with total page 275 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational intelligence techniques have enjoyed growing interest in recent decades among the earth and environmental science research communities for their powerful ability to solve and understand various complex problems and develop novel approaches toward a sustainable earth. This book compiles a collection of recent developments and rigorous applications of computational intelligence in these disciplines. Techniques covered include artificial neural networks, support vector machines, fuzzy logic, decision-making algorithms, supervised and unsupervised classification algorithms, probabilistic computing, hybrid methods and morphic computing. Further topics given treatment in this volume include remote sensing, meteorology, atmospheric and oceanic modeling, climate change, environmental engineering and management, catastrophic natural hazards, air and environmental pollution and water quality. By linking computational intelligence techniques with earth and environmental science oriented problems, this book promotes synergistic activities among scientists and technicians working in areas such as data mining and machine learning. We believe that a diverse group of academics, scientists, environmentalists, meteorologists and computing experts with a common interest in computational intelligence techniques within the earth and environmental sciences will find this book to be of great value.

Download or read book Computers in Earth and Environmental Sciences written by Hamid Reza Pourghasemi and published by Elsevier. This book was released on 2021-09-22 with total page 704 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computers in Earth and Environmental Sciences: Artificial Intelligence and Advanced Technologies in Hazards and Risk Management addresses the need for a comprehensive book that focuses on multi-hazard assessments, natural and manmade hazards, and risk management using new methods and technologies that employ GIS, artificial intelligence, spatial modeling, machine learning tools and meta-heuristic techniques. The book is clearly organized into four parts that cover natural hazards, environmental hazards, advanced tools and technologies in risk management, and future challenges in computer applications to hazards and risk management. Researchers and professionals in Earth and Environmental Science who require the latest technologies and advances in hazards, remote sensing, geosciences, spatial modeling and machine learning will find this book to be an invaluable source of information on the latest tools and technologies available. Covers advanced tools and technologies in risk management of hazards in both the Earth and Environmental Sciences Details the benefits and applications of various technologies to assist researchers in choosing the most appropriate techniques for purpose Expansively covers specific future challenges in the use of computers in Earth and Environmental Science Includes case studies that detail the applications of the discussed technologies down to individual hazards

Download or read book Machine Learning Methods in the Environmental Sciences written by William Wei Hsieh and published by . This book was released on 2014-05-14 with total page 365 pages. Available in PDF, EPUB and Kindle. Book excerpt: A graduate textbook that provides a unified treatment of machine learning methods and their applications in the environmental sciences.

Download or read book Artificial Neural Networks in Biological and Environmental Analysis written by Grady Hanrahan and published by CRC Press. This book was released on 2011-01-18 with total page 206 pages. Available in PDF, EPUB and Kindle. Book excerpt: Originating from models of biological neural systems, artificial neural networks (ANN) are the cornerstones of artificial intelligence research. Catalyzed by the upsurge in computational power and availability, and made widely accessible with the co-evolution of software, algorithms, and methodologies, artificial neural networks have had a profound

Download or read book Data Science Applied to Sustainability Analysis written by Jennifer Dunn and published by Elsevier. This book was released on 2021-05-11 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Science Applied to Sustainability Analysis focuses on the methodological considerations associated with applying this tool in analysis techniques such as lifecycle assessment and materials flow analysis. As sustainability analysts need examples of applications of big data techniques that are defensible and practical in sustainability analyses and that yield actionable results that can inform policy development, corporate supply chain management strategy, or non-governmental organization positions, this book helps answer underlying questions. In addition, it addresses the need of data science experts looking for routes to apply their skills and knowledge to domain areas. Presents data sources that are available for application in sustainability analyses, such as market information, environmental monitoring data, social media data and satellite imagery Includes considerations sustainability analysts must evaluate when applying big data Features case studies illustrating the application of data science in sustainability analyses

Download or read book Deep Learning for the Earth Sciences written by Gustau Camps-Valls and published by John Wiley & Sons. This book was released on 2021-08-18 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Artificial Intelligence Methods Applied to Urban Remote Sensing and GIS written by Chang-Wook Lee and published by Mdpi AG. This book was released on 2021-11-11 with total page 166 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is based on Special Issue "Artificial Intelligence Methods Applied to Urban Remote Sensing and GIS" from early 2020 to 2021. This book includes seven papers related to the application of artificial intelligence, machine learning and deep learning algorithms using remote sensing and GIS techniques in urban areas.

Download or read book Artificial Intelligence in Earth Science written by Ziheng Sun and published by Elsevier. This book was released on 2023-04-27 with total page 430 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book Artificial Intelligence and Modeling for Water Sustainability written by Alaa El Din Mahmoud and published by CRC Press. This book was released on 2023-04-25 with total page 345 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial intelligence and the use of computational methods to extract information from data are providing adequate tools to monitor and predict water pollutants and water quality issues faster and more accurately. Smart sensors and machine learning models help detect and monitor dispersion and leakage of pollutants before they reach groundwater. With contributions from experts in academia and industries, who give a unified treatment of AI methods and their applications in water science, this book help governments, industries, and homeowners not only address water pollution problems more quickly and efficiently, but also gain better insight into the implementation of more effective remedial measures. FEATURES Provides cutting-edge AI applications in water sector. Highlights the environmental models used by experts in different countries. Discusses various types of models using AI and its tools for achieving sustainable development in water and groundwater. Includes case studies and recent research directions for environmental issues in water sector. Addresses future aspects and innovation in AI field related to watersustainability. This book will appeal to scientists, researchers, and undergraduate and graduate students majoring in environmental or computer science and industry professionals in water science and engineering, environmental management, and governmental sectors. It showcases artificial intelligence applications in detecting environmental issues, with an emphasis on the mitigation and conservation of water and underground resources.

Download or read book Reshaping Environmental Science Through Machine Learning and IoT written by Gupta, Rajeev Kumar and published by IGI Global. This book was released on 2024-05-06 with total page 459 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the face of escalating environmental challenges such as climate change, air and water pollution, and natural disasters, traditional approaches to understanding and addressing these issues have yet to be proven sufficient. Academic scholars are compelled to seek innovative solutions that marry digital intelligence and natural ecosystems. Reshaping Environmental Science Through Machine Learning and IoT serves as a comprehensive exploration into the transformative potential of Machine Learning (ML) and the Internet of Things (IoT) to address critical environmental challenges. The book establishes a robust foundation in ML and IoT, explaining their relevance to environmental science. As the narrative unfolds, it delves into diverse applications, providing theoretical insights alongside practical knowledge. From interpreting weather patterns to predicting air and water quality, the book navigates through the intricate web of environmental complexities. Notably, it unveils approaches to disaster management, waste sorting, and climate change monitoring, showcasing the symbiotic relationship between digital intelligence and natural ecosystems. This book is ideal for audiences from students and researchers to data scientists and disaster management professionals with a nuanced understanding of IoT, ML, and Artificial Intelligence (AI).

Download or read book Handbook of Research on Artificial Intelligence Techniques and Algorithms written by Vasant, Pandian and published by IGI Global. This book was released on 2014-11-30 with total page 873 pages. Available in PDF, EPUB and Kindle. Book excerpt: For decades, optimization methods such as Fuzzy Logic, Artificial Neural Networks, Firefly, Simulated annealing, and Tabu search, have been capable of handling and tackling a wide range of real-world application problems in society and nature. Analysts have turned to these problem-solving techniques in the event during natural disasters and chaotic systems research. The Handbook of Research on Artificial Intelligence Techniques and Algorithms highlights the cutting edge developments in this promising research area. This premier reference work applies Meta-heuristics Optimization (MO) Techniques to real world problems in a variety of fields including business, logistics, computer science, engineering, and government. This work is particularly relevant to researchers, scientists, decision-makers, managers, and practitioners.

Download or read book Intelligence Systems for Earth Environmental and Planetary Sciences written by Hossein Bonakdari and published by Elsevier. This book was released on 2024-07-30 with total page 552 pages. Available in PDF, EPUB and Kindle. Book excerpt: Intelligence Systems for Earth, Environmental and Planetary Sciences: Methods, Models and Applications provides cutting-edge theory and applications of modern-day artificial intelligence and data science in the Earth, environment, and planetary science fields. The book is divided into three sections: (i) Methods, covering the fundamentals of intelligence systems, along with an introduction to the preparation of datasets; (ii) Models, detailing model development, data assimilation, and techniques in each field; and (iii) Applications, presenting case studies of artificial intelligence and data science solutions to Earth, environmental, and planetary sciences problems, as well as future perspectives. Intelligence Systems for Earth, Environmental and Planetary Sciences will be of interest to students, academics, and postgraduate professionals in the field of applied sciences, Earth, environmental, and planetary sciences and would also serve as an excellent companion resource to courses studying artificial intelligence applications for theoretical and practical studies in Earth, environmental, and planetary sciences. Facilitates the application of artificial intelligence and data science systems to create comprehensive methodologies for analyzing, processing, predicting, and management strategies in the fields of Earth, environment, and planetary science Developed with an interdisciplinary framework, with an aim to promote artificial intelligence models for real-time Earth systems Includes a section on case studies of artificial intelligence and data science solutions to Earth, environmental, and planetary sciences problems, as well as future perspectives

Download or read book Artificial Intelligence Theory and Applications written by Endre Pap and published by Springer Nature. This book was released on 2021-07-15 with total page 353 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is an up-to-date collection, in AI and environmental research, related to the project ATLAS. AI is used for gaining an understanding of complex research phenomena in the environmental sciences, encompassing heterogeneous, noisy, inaccurate, uncertain, diverse spatio-temporal data and processes. The first part of the book covers new mathematics in the field of AI: aggregation functions with special classes such as triangular norms and copulas, pseudo-analysis, and the introduction to fuzzy systems and decision making. Generalizations of the Choquet integral with applications in decision making as CPT are presented. The second part of the book is devoted to AI in the geo-referenced air pollutants and meteorological data, image processing, machine learning, neural networks, swarm intelligence, robotics, mental well-being and data entry errors. The book is intended for researchers in AI and experts in environmental sciences as well as for Ph.D. students.

Download or read book Statistical Methods for Trend Detection and Analysis in the Environmental Sciences written by Richard Chandler and published by John Wiley & Sons. This book was released on 2011-03-25 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: The need to understand and quantify change is fundamental throughout the environmental sciences. This might involve describing past variation, understanding the mechanisms underlying observed changes, making projections of possible future change, or monitoring the effect of intervening in some environmental system. This book provides an overview of modern statistical techniques that may be relevant in problems of this nature. Practitioners studying environmental change will be familiar with many classical statistical procedures for the detection and estimation of trends. However, the ever increasing capacity to collect and process vast amounts of environmental information has led to growing awareness that such procedures are limited in the insights that they can deliver. At the same time, significant developments in statistical methodology have often been widely dispersed in the statistical literature and have therefore received limited exposure in the environmental science community. This book aims to provide a thorough but accessible review of these developments. It is split into two parts: the first provides an introduction to this area and the second part presents a collection of case studies illustrating the practical application of modern statistical approaches to the analysis of trends in real studies. Key Features: Presents a thorough introduction to the practical application and methodology of trend analysis in environmental science. Explores non-parametric estimation and testing as well as parametric techniques. Methods are illustrated using case studies from a variety of environmental application areas. Looks at trends in all aspects of a process including mean, percentiles and extremes. Supported by an accompanying website featuring datasets and R code. The book is designed to be accessible to readers with some basic statistical training, but also contains sufficient detail to serve as a reference for practising statisticians. It will therefore be of use to postgraduate students and researchers both in the environmental sciences and in statistics.