Big Data In Astronomy
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Knowledge Discovery In Big Data From Astronomy And Earth Observation
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Author : Petr Skoda
language : en
Publisher: Elsevier
Release Date : 2020-04-10
Knowledge Discovery In Big Data From Astronomy And Earth Observation written by Petr Skoda and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-10 with Computers categories.
Knowledge Discovery in Big Data from Astronomy and Earth Observation: Astrogeoinformatics bridges the gap between astronomy and geoscience in the context of applications, techniques and key principles of big data. Machine learning and parallel computing are increasingly becoming cross-disciplinary as the phenomena of Big Data is becoming common place. This book provides insight into the common workflows and data science tools used for big data in astronomy and geoscience. After establishing similarity in data gathering, pre-processing and handling, the data science aspects are illustrated in the context of both fields. Software, hardware and algorithms of big data are addressed. Finally, the book offers insight into the emerging science which combines data and expertise from both fields in studying the effect of cosmos on the earth and its inhabitants. - Addresses both astronomy and geosciences in parallel, from a big data perspective - Includes introductory information, key principles, applications and the latest techniques - Well-supported by computing and information science-oriented chapters to introduce the necessary knowledge in these fields
Statistics Data Mining And Machine Learning In Astronomy
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Author : Željko Ivezić
language : en
Publisher: Princeton University Press
Release Date : 2014-01-12
Statistics Data Mining And Machine Learning In Astronomy written by Željko Ivezić and has been published by Princeton University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-01-12 with Science categories.
As telescopes, detectors, and computers grow ever more powerful, the volume of data at the disposal of astronomers and astrophysicists will enter the petabyte domain, providing accurate measurements for billions of celestial objects. This book provides a comprehensive and accessible introduction to the cutting-edge statistical methods needed to efficiently analyze complex data sets from astronomical surveys such as the Panoramic Survey Telescope and Rapid Response System, the Dark Energy Survey, and the upcoming Large Synoptic Survey Telescope. It serves as a practical handbook for graduate students and advanced undergraduates in physics and astronomy, and as an indispensable reference for researchers. Statistics, Data Mining, and Machine Learning in Astronomy presents a wealth of practical analysis problems, evaluates techniques for solving them, and explains how to use various approaches for different types and sizes of data sets. For all applications described in the book, Python code and example data sets are provided. The supporting data sets have been carefully selected from contemporary astronomical surveys (for example, the Sloan Digital Sky Survey) and are easy to download and use. The accompanying Python code is publicly available, well documented, and follows uniform coding standards. Together, the data sets and code enable readers to reproduce all the figures and examples, evaluate the methods, and adapt them to their own fields of interest. Describes the most useful statistical and data-mining methods for extracting knowledge from huge and complex astronomical data sets Features real-world data sets from contemporary astronomical surveys Uses a freely available Python codebase throughout Ideal for students and working astronomers
Astrostatistics
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Author : Gutti Jogesh Babu
language : en
Publisher: CRC Press
Release Date : 1996-08-01
Astrostatistics written by Gutti Jogesh Babu and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996-08-01 with Mathematics categories.
Modern astronomers encounter a vast range of challenging statistical problems, yet few are familiar with the wealth of techniques developed by statisticians. Conversely, few statisticians deal with the compelling problems confronted in astronomy. Astrostatistics bridges this gap. Authored by a statistician-astronomer team, it provides professionals and advanced students in both fields with exposure to issues of mutual interest. In the first half of the book the authors introduce statisticians to stellar, galactic, and cosmological astronomy and discuss the complex character of astronomical data. For astronomers, they introduce the statistical principles of nonparametrics, multivariate analysis, time series analysis, density estimation, and resampling methods. The second half of the book is organized by statistical topic. Each chapter contains examples of problems encountered astronomical research and highlights methodological issues. The final chapter explores some controversial issues in astronomy that have a strong statistical component. The authors provide an extensive bibliography and references to software for implementing statistical methods. The "marriage" of astronomy and statistics is a natural one and benefits both disciplines. Astronomers need the tools and methods of statistics to interpret the vast amount of data they generate, and the issues related to astronomical data pose intriguing challenges for statisticians. Astrostatistics paves the way to improved statistical analysis of astronomical data and provides a common ground for future collaboration between the two fields.
Big Data
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Author : Viktor Mayer-Schonberger
language : en
Publisher: Hachette UK
Release Date : 2013-03-14
Big Data written by Viktor Mayer-Schonberger and has been published by Hachette UK this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-14 with Business & Economics categories.
New and expanded edition. An International Bestseller - Over One Million Copies Sold! Shortlisted for the Financial Times/Goldman Sachs Business Book of the Year Award. Since Aristotle, we have fought to understand the causes behind everything. But this ideology is fading. In the age of big data, we can crunch an incomprehensible amount of information, providing us with invaluable insights about the what rather than the why. We're just starting to reap the benefits: tracking vital signs to foresee deadly infections, predicting building fires, anticipating the best moment to buy a plane ticket, seeing inflation in real time and monitoring social media in order to identify trends. But there is a dark side to big data. Will it be machines, rather than people, that make the decisions? How do you regulate an algorithm? What will happen to privacy? Will individuals be punished for acts they have yet to commit? In this groundbreaking and fascinating book, two of the world's most-respected data experts reveal the reality of a big data world and outline clear and actionable steps that will equip the reader with the tools needed for this next phase of human evolution.
Big Data Mining For Climate Change
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Author : Zhihua Zhang
language : en
Publisher: Elsevier
Release Date : 2019-11-20
Big Data Mining For Climate Change written by Zhihua Zhang and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-20 with Science categories.
Climate change mechanisms, impacts, risks, mitigation, adaption, and governance are widely recognized as the biggest, most interconnected problem facing humanity. Big Data Mining for Climate Change addresses one of the fundamental issues facing scientists of climate or the environment: how to manage the vast amount of information available and analyse it. The resulting integrated and interdisciplinary big data mining approaches are emerging, partially with the help of the United Nation's big data climate challenge, some of which are recommended widely as new approaches for climate change research. Big Data Mining for Climate Change delivers a rich understanding of climate-related big data techniques and highlights how to navigate huge amount of climate data and resources available using big data applications. It guides future directions and will boom big-data-driven researches on modeling, diagnosing and predicting climate change and mitigating related impacts. This book mainly focuses on climate network models, deep learning techniques for climate dynamics, automated feature extraction of climate variability, and sparsification of big climate data. It also includes a revelatory exploration of big-data-driven low-carbon economy and management. Its content provides cutting-edge knowledge for scientists and advanced students studying climate change from various disciplines, including atmospheric, oceanic and environmental sciences; geography, ecology, energy, economics, management, engineering, and public policy.
Mobility Patterns Big Data And Transport Analytics
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Author : Constantinos Antoniou
language : en
Publisher: Elsevier
Release Date : 2025-06-01
Mobility Patterns Big Data And Transport Analytics written by Constantinos Antoniou and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-01 with Business & Economics categories.
Mobility Patterns, Big Data and Transport Analytics: Tools and Applications for Modeling, Second Edition provides a guide to the new analytical framework and its relation to big data, focusing on capturing, predicting, visualizing, and controlling mobility patterns-a key aspect of transportation modeling. The book features prominent international experts who provide overviews on new analytical frameworks, applications, and concepts in mobility analysis and transportation systems. Fields covered are evolving rapidly, and this new edition updates existing material and provides new chapters that reflect recent developments in the field (such as the emergence of active, transfer and reinforcement learning). Users will find a detailed, mobility ‘structural’ analysis and a look at the extensive behavioral characteristics of transport, observability requirements, limitations for realistic transportation applications, and transportation systems analysis that are related to complex processes and phenomena. This book bridges the gap between big data, data science, and transportation systems analysis with a study of big data’s impact on mobility and an introduction to the tools necessary to apply new techniques.
Ai And The Revival Of Big Data
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Author : Ayyalasomayajula, Madan Mohan Tito
language : en
Publisher: IGI Global
Release Date : 2025-02-05
Ai And The Revival Of Big Data written by Ayyalasomayajula, Madan Mohan Tito and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-05 with Computers categories.
The interplay between big data and Artificial Intelligence has redefined how organizations process, analyze, and utilize information in the modern era. By leveraging AI, big data has transitioned from a static resource to a dynamic force capable of driving innovation, creating strategic insights, and transforming industries. This evolution underscores the importance of building trust in both human and technological systems to manage data responsibly and effectively. As the reliance on data-driven decision-making grows, understanding this relationship is vital for advancing societal progress and fostering sustainable development. AI and the Revival of Big Data offers a nuanced understanding of the evolution of big data and its enduring significance in the digital age. Additionally, the discussion of AI's role in revitalizing big data will inspire new avenues of research and collaboration across disciplines. Covering topics such as load distribution, financial malfeasance, image analysis, this book is an excellent resource for data scientists, business leaders, practitioners, policymakers, and industry professionals, professionals, researchers, scholars, academicians, and more.
Chatgpt For Astronomers
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Author : Jade Summers
language : en
Publisher: Jade Summers
Release Date :
Chatgpt For Astronomers written by Jade Summers and has been published by Jade Summers this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
🚀 Unlock the Stars with AI! 🌌 Embark on a journey through the cosmos with ChatGPT for Astronomers: Unlocking the Universe of AI! Whether you're a seasoned stargazer or just curious about the night sky, this groundbreaking guide bridges the gap between astronomy and artificial intelligence. Discover how tools like ChatGPT can transform how we explore, analyze, and communicate the mysteries of the universe. ✨ Highlights: Learn AI fundamentals and their applications in astronomy 🌠 Explore how ChatGPT aids in data analysis and celestial discoveries 🔭 Dive into case studies and real-world applications of AI in astronomy 🌍 Get inspired by ways to use AI for stargazing and public engagement 🌟 Overcome the challenges of integrating AI into research projects 🛠️ Ready to unlock the universe? Your adventure into the stars awaits! 🪐
Big Data Management Technologies And Applications
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Author : Hu, Wen-Chen
language : en
Publisher: IGI Global
Release Date : 2013-10-31
Big Data Management Technologies And Applications written by Hu, Wen-Chen and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-10-31 with Computers categories.
"This book discusses the exponential growth of information size and the innovative methods for data capture, storage, sharing, and analysis for big data"--Provided by publisher.
Deep Learning In Solar Astronomy
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Author : Long Xu
language : en
Publisher: Springer Nature
Release Date : 2022-05-27
Deep Learning In Solar Astronomy written by Long Xu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-27 with Science categories.
The volume of data being collected in solar astronomy has exponentially increased over the past decade and we will be entering the age of petabyte solar data. Deep learning has been an invaluable tool exploited to efficiently extract key information from the massive solar observation data, to solve the tasks of data archiving/classification, object detection and recognition. Astronomical study starts with imaging from recorded raw data, followed by image processing, such as image reconstruction, inpainting and generation, to enhance imaging quality. We study deep learning for solar image processing. First, image deconvolution is investigated for synthesis aperture imaging. Second, image inpainting is explored to repair over-saturated solar image due to light intensity beyond threshold of optical lens. Third, image translation among UV/EUV observation of the chromosphere/corona, Ha observation of the chromosphere and magnetogram of the photosphere is realized by using GAN, exhibiting powerful image domain transfer ability among multiple wavebands and different observation devices. It can compensate the lack of observation time or waveband. In addition, time series model, e.g., LSTM, is exploited to forecast solar burst and solar activity indices. This book presents a comprehensive overview of the deep learning applications in solar astronomy. It is suitable for the students and young researchers who are major in astronomy and computer science, especially interdisciplinary research of them.