Data Mining Predicting Tipping Points
DOWNLOAD
Download Data Mining Predicting Tipping Points PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Data Mining Predicting Tipping Points book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Data Mining Predicting Tipping Points
DOWNLOAD
Author : Dr. Philip Gordon, PhD
language : en
Publisher: Lulu.com
Release Date : 2013-01-31
Data Mining Predicting Tipping Points written by Dr. Philip Gordon, PhD and has been published by Lulu.com this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-01-31 with Political Science categories.
Tipping Points as evidenced in global events are, in many ways, influenced by media. DATA MINING for predicting and analyzing world events. This just released, ground-breaking book: DATA MINING: PREDICTING TIPPING POINTS by Dr Philip Gordon, Ph.D, details three case studies which were selected on the basis of common Tipping Point Attributes: Each involved media contagiousness and stickiness during their development and, each arrived at a "dramatic moment in time," which could only be characterized by the phenomenon of Tipping Points. Three recent case studies explore the leading edge technologies of DATA MINING and the theory of TIPPING POINTS: The first case study, the 2008 Presidential Campaign of Barack Obama was chosen to examine a narrower scope and timeframe for the application of the analysis. In contrast to the second case study, the International Financial Crisis of 2007-2010, which involves a broader data study period to identify trends and more complex issues. The third study, Climate Change was included as consideration because the data mining research and analysis revealed critical relationships between Media Impact and Global Events. As the issue of Climate Change is still evolving, Dr Gordon provides a Data Mining and Tipping Point Theory methodology for analyzing and predicting our planets' most pressing Global Tipping Points. Review Comments: "The genius of the formulation of DATA MINING: PREDICTING TIPPING POINTS is that it takes explicit account of the role of social media and the internet at facilitating bifurcations and promoting dynamical instability. In effect, we have trimmed a few feet of tail off the kite. As a reader, I was informed and educated as to the factors which conspire to influence stability / instability in complex social systems. ...the book does a good job of making sense of past bifurcations and dynamical instabilities, namely political instability, our perception of global climate change, and international economic crises...my compliments on a truly insightful Media Tipping Points." -Prof. Dr. (med.) Peter S. Geissler, A.B., B.S., M.S., M.Phil., Ph.D. (Yale) M.A., M.Eng., M.S., Ph.D., M.S., M.D., M.Phil.(Cantab) "A truly fascinating book that (teaches) a whole new way of thinking about major events and how the media can influence them. - Being a political junkie I was heavily into the media coverage of the 2008 Obama election and the global financial meltdown both via TV and the blogosphere. I now find myself looking for the tipping points and stickiness factors as other key events unfold. Usually, I have trouble reading theoretical books but this one was an easy read and if you want supporting data then the references are there. This could become a solid reference for those in the media who truly want to understand what they are reporting. Highly recommended and I look forward to Dr. Gordon's ongoing analysis of (future) events." -Dr. Ralph Moorhouse, Ph.D. Political junkie, Expert: natural polymers for industries "The application of Data Mining and Tipping Point Theory to media and global events, particularly the financial crisis and climate change, is a fascinating one." -Dr. Serge Besanger, PhD Expert, International Monetary Fund ..".very interesting application (of the Tipping Point Theory)...potential opportunity for predicting other global events, i.e.: Egyptian crisis and perhaps, even terrorism activities." -Dr. Adam AJLANI, PhD Professor, Sciences Politic and Political Consultant, France TV1
Handbook Of Mobility Data Mining Volume 2
DOWNLOAD
Author : Haoran Zhang
language : en
Publisher: Elsevier
Release Date : 2023-01-29
Handbook Of Mobility Data Mining Volume 2 written by Haoran Zhang and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-29 with Business & Economics categories.
Handbook of Mobility Data Mining, Volume Two: Mobility Analytics and Prediction introduces the fundamental technologies of mobile big data mining (MDM), advanced AI methods, and upper-level applications, helping readers comprehensively understand MDM with a bottom-up approach. The book explains how to preprocess mobile big data, visualize urban mobility, simulate and predict human travel behavior, and assess urban mobility characteristics and their matching performance as conditions and constraints in transport, emergency management, and sustainability development systems. The book introduces how to design MDM platforms that adapt to the evolving mobility environment and new types of transportation and users. This helpful guide provides a basis for how to simulate and predict mobility data. After an introductory theory chapter, the book then covers crucial topics such as long-term mobility pattern analytics, mobility data generators, user information inference, Grid-based population density prediction, and more. The book concludes with a chapter on graph-based mobility data analytics. The information in this work is crucial for researchers, engineers, operators, company administrators, and policymakers in related fields, to comprehensively understand current technologies' infra-knowledge structure and limitations. - Discusses how to efficiently simulate massive and large-scale people movement and predict mobility at an urban scale - Introduces both online detection methods, which can sequentially process data, and offline detection methods, which are usually more robust - Stems from the editor's strong network of global transport authorities and transport companies, providing a solid knowledge structure and data foundation as well as geographical and stakeholder coverage
Data Mining Models
DOWNLOAD
Author : Ravi Deshpande
language : en
Publisher: Educohack Press
Release Date : 2025-02-20
Data Mining Models written by Ravi Deshpande and has been published by Educohack Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-20 with Business & Economics categories.
In today's tech industry, big data is the biggest buzz. Have you ever wondered how platforms like Facebook and Twitter handle millions of user data seamlessly? This book unveils the secrets behind those techniques. We explore data mining models and techniques, weighing their pros and cons to determine the best-suited model for efficient data processing. This comprehensive guide provides detailed insights into data mining processes, enhanced with hands-on coding examples to offer an exclusive learning experience. Delve into the world of data and uncover the mechanisms that power modern technology!
Applied Data Mining For Forecasting Using Sas
DOWNLOAD
Author : Tim Rey
language : en
Publisher: SAS Institute
Release Date : 2012-07-31
Applied Data Mining For Forecasting Using Sas written by Tim Rey and has been published by SAS Institute this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-07-31 with Computers categories.
Applied Data Mining for Forecasting Using SAS, by Tim Rey, Arthur Kordon, and Chip Wells, introduces and describes approaches for mining large time series data sets. Written for forecasting practitioners, engineers, statisticians, and economists, the book details how to select useful candidate input variables for time series regression models in environments when the number of candidates is large, and identifies the correlation structure between selected candidate inputs and the forecast variable.
Computational Data And Social Networks
DOWNLOAD
Author : Janos Kertesz
language : en
Publisher: Springer Nature
Release Date : 2025-06-06
Computational Data And Social Networks written by Janos Kertesz and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-06 with Computers categories.
This book constitutes the refereed conference proceedings of the 13th International Conference on Computational Data and Social Networks, CSoNet 2024, held in Bangkok, Thailand, during December 16–18, 2024. The 18 full papers and 17 short papers presented in this volume were carefully reviewed and selected from 50 submissions. These papers deal with various aspects of computational data and social networks, focusing on large-scale network computing, data network analysis, mining, security and privacy, optimization, and learning.
Addressing Tipping Points For A Precarious Future
DOWNLOAD
Author : Timothy O'Riordan
language : en
Publisher: Oxford University Press
Release Date : 2013-08-22
Addressing Tipping Points For A Precarious Future written by Timothy O'Riordan and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-08-22 with Business & Economics categories.
Tipping points are zones or thresholds of profound changes in natural or social conditions with very considerable and largely unforecastable consequences. Tipping points may be dangerous for societies and economies, especially if the prevailing governing arrangements are not designed either to anticipate them or adapt to their arrival. Tipping points can also be transformational of cultures and behaviours so that societies can learn to adapt and to alter their outlooks and mores in favour of accommodating to more sustainable ways of living. This volume examines scientific, economic and social analyses of tipping points, and the spiritual and creative approaches to identifying and anticipating them. The authors focus on climate change, ice melt, tropical forest drying and alterations in oceanic and atmospheric circulations. They also look closely at various aspects of human use of the planet, especially food production, and at the loss of biodiversity, where alterations to natural cycles may be creating convulsive couplings of tipping points. They survey the various institutional aspects of politics, economics, culture and religion to see why such dangers persist.
Commercial Data Mining
DOWNLOAD
Author : David Nettleton
language : en
Publisher: Elsevier
Release Date : 2014-01-29
Commercial Data Mining written by David Nettleton and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-01-29 with Computers categories.
Whether you are brand new to data mining or working on your tenth predictive analytics project, Commercial Data Mining will be there for you as an accessible reference outlining the entire process and related themes. In this book, you'll learn that your organization does not need a huge volume of data or a Fortune 500 budget to generate business using existing information assets. Expert author David Nettleton guides you through the process from beginning to end and covers everything from business objectives to data sources, and selection to analysis and predictive modeling. Commercial Data Mining includes case studies and practical examples from Nettleton's more than 20 years of commercial experience. Real-world cases covering customer loyalty, cross-selling, and audience prediction in industries including insurance, banking, and media illustrate the concepts and techniques explained throughout the book. - Illustrates cost-benefit evaluation of potential projects - Includes vendor-agnostic advice on what to look for in off-the-shelf solutions as well as tips on building your own data mining tools - Approachable reference can be read from cover to cover by readers of all experience levels - Includes practical examples and case studies as well as actionable business insights from author's own experience
Machine Learning Algorithms And Applications In Engineering
DOWNLOAD
Author : Prasenjit Chatterjee
language : en
Publisher: CRC Press
Release Date : 2023-02-28
Machine Learning Algorithms And Applications In Engineering written by Prasenjit Chatterjee and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-02-28 with Computers categories.
Machine Learning (ML) is a sub field of artificial intelligence that uses soft computing and algorithms to enable computers to learn on their own and identify patterns in observed data, build models that explain the world, and predict things without having explicit pre-programmed rules and models. This book discusses various applications of ML in engineering fields and the use of ML algorithms in solving challenging engineering problems ranging from biomedical, transport, supply chain and logistics, to manufacturing and industrial. Through numerous case studies, it will assist researchers and practitioners in selecting the correct options and strategies for managing organizational tasks.
Internet Of Things And Data Analytics Handbook
DOWNLOAD
Author : Hwaiyu Geng
language : en
Publisher: John Wiley & Sons
Release Date : 2017-01-10
Internet Of Things And Data Analytics Handbook written by Hwaiyu Geng 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 2017-01-10 with Technology & Engineering categories.
This book examines the Internet of Things (IoT) and Data Analytics from a technical, application, and business point of view. Internet of Things and Data Analytics Handbook describes essential technical knowledge, building blocks, processes, design principles, implementation, and marketing for IoT projects. It provides readers with knowledge in planning, designing, and implementing IoT projects. The book is written by experts on the subject matter, including international experts from nine countries in the consumer and enterprise fields of IoT. The text starts with an overview and anatomy of IoT, ecosystem of IoT, communication protocols, networking, and available hardware, both present and future applications and transformations, and business models. The text also addresses big data analytics, machine learning, cloud computing, and consideration of sustainability that are essential to be both socially responsible and successful. Design and implementation processes are illustrated with best practices and case studies in action. In addition, the book: Examines cloud computing, data analytics, and sustainability and how they relate to IoT overs the scope of consumer, government, and enterprise applications Includes best practices, business model, and real-world case studies Hwaiyu Geng, P.E., is a consultant with Amica Research (www.AmicaResearch.org, Palo Alto, California), promoting green planning, design, and construction projects. He has had over 40 years of manufacturing and management experience, working with Westinghouse, Applied Materials, Hewlett Packard, and Intel on multi-million high-tech projects. He has written and presented numerous technical papers at international conferences. Mr. Geng, a patent holder, is also the editor/author of Data Center Handbook (Wiley, 2015).
Optimized Predictive Models In Health Care Using Machine Learning
DOWNLOAD
Author : Sandeep Kumar
language : en
Publisher: John Wiley & Sons
Release Date : 2024-03-12
Optimized Predictive Models In Health Care Using Machine Learning written by Sandeep Kumar 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 2024-03-12 with Computers categories.
OPTIMIZED PREDICTIVE MODELS IN HEALTH CARE USING MACHINE LEARNING This book is a comprehensive guide to developing and implementing optimized predictive models in healthcare using machine learning and is a required resource for researchers, healthcare professionals, and students who wish to know more about real-time applications. The book focuses on how humans and computers interact to ever-increasing levels of complexity and simplicity and provides content on the theory of optimized predictive model design, evaluation, and user diversity. Predictive modeling, a field of machine learning, has emerged as a powerful tool in healthcare for identifying high-risk patients, predicting disease progression, and optimizing treatment plans. By leveraging data from various sources, predictive models can help healthcare providers make informed decisions, resulting in better patient outcomes and reduced costs. Other essential features of the book include: provides detailed guidance on data collection and preprocessing, emphasizing the importance of collecting accurate and reliable data; explains how to transform raw data into meaningful features that can be used to improve the accuracy of predictive models; gives a detailed overview of machine learning algorithms for predictive modeling in healthcare, discussing the pros and cons of different algorithms and how to choose the best one for a specific application; emphasizes validating and evaluating predictive models; provides a comprehensive overview of validation and evaluation techniques and how to evaluate the performance of predictive models using a range of metrics; discusses the challenges and limitations of predictive modeling in healthcare; highlights the ethical and legal considerations that must be considered when developing predictive models and the potential biases that can arise in those models. Audience The book will be read by a wide range of professionals who are involved in healthcare, data science, and machine learning.