big data mining for climate change

Big Data Mining For Climate Change
Author: Zhihua Zhang
Publisher:
Release Date: 2019-12
Pages: 344
ISBN:
Available Language: English, Spanish, And French
EBOOK SYNOPSIS:

Big Data Mining for Climate Change addresses how to manage the vast amount of information available for analysis. Climate change and its environmental, economic and social consequences are widely recognized as the biggest, most interconnected problem facing humanity. There is a huge amount of potential information currently available...and it is growing exponentially. This book walks through the latest research and how to navigate the resources available using big data applications. It is appropriate for scientists and advanced students studying climate change from a number of disciplines, including the atmospheric sciences, oceanic sciences, geography, environment sciences, ecology, energy, economics, engineering and public policy. Provides a step-by-step guide for applying big data mining tools to climate and environmental research Presents a comprehensive review of theory and algorithms of big data mining for climate change Includes current research in climate and environmental science as it relates to using big data algorithms

Data Mining And Knowledge Discovery For Big Data
Author: Wesley W. Chu
Publisher: Springer Science & Business Media
Release Date: 2013-09-24
Pages: 311
ISBN:
Available Language: English, Spanish, And French
EBOOK SYNOPSIS:

The field of data mining has made significant and far-reaching advances over the past three decades. Because of its potential power for solving complex problems, data mining has been successfully applied to diverse areas such as business, engineering, social media, and biological science. Many of these applications search for patterns in complex structural information. In biomedicine for example, modeling complex biological systems requires linking knowledge across many levels of science, from genes to disease. Further, the data characteristics of the problems have also grown from static to dynamic and spatiotemporal, complete to incomplete, and centralized to distributed, and grow in their scope and size (this is known as big data). The effective integration of big data for decision-making also requires privacy preservation. The contributions to this monograph summarize the advances of data mining in the respective fields. This volume consists of nine chapters that address subjects ranging from mining data from opinion, spatiotemporal databases, discriminative subgraph patterns, path knowledge discovery, social media, and privacy issues to the subject of computation reduction via binary matrix factorization.

Data Mining And Big Data
Author: Ying Tan
Publisher: Springer
Release Date: 2017-07-18
Pages: 546
ISBN:
Available Language: English, Spanish, And French
EBOOK SYNOPSIS:

This book constitutes the refereed proceedings of the Second International Conference on Data Mining and Big Data, DMBD 2017, held in Fukuoka, Japan, in July/August 2017. The 53 papers presented in this volume were carefully reviewed and selected from 96 submissions. They were organized in topical sections named: association analysis; clustering; prediction; classification; schedule and sequence analysis; big data; data analysis; data mining; text mining; deep learning; high performance computing; knowledge base and its framework; and fuzzy control.

Thinking Big Data In Geography
Author: Jim Thatcher
Publisher: U of Nebraska Press
Release Date: 2018-04
Pages: 324
ISBN:
Available Language: English, Spanish, And French
EBOOK SYNOPSIS:

Thinking Big Data in Geography offers a practical state-of-the-field overview of big data as both a means and an object of research, with essays from prominent and emerging scholars such as Rob Kitchin, Renee Sieber, and Mark Graham. Part 1 explores how the advent of geoweb technologies and big data sets has influenced some of geography’s major subdisciplines: urban politics and political economy, human-environment interactions, and geographic information sciences. Part 2 addresses how the geographic study of big data has implications for other disciplinary fields, notably the digital humanities and the study of social justice. The volume concludes with theoretical applications of the geoweb and big data as they pertain to society as a whole, examining the ways in which user-generated data come into the world and are complicit in its unfolding. The contributors raise caution regarding the use of spatial big data, citing issues of accuracy, surveillance, and privacy.

Advances In Knowledge Discovery And Data Mining
Author: Vincent S. Tseng
Publisher: Springer
Release Date: 2014-05-08
Pages: 622
ISBN:
Available Language: English, Spanish, And French
EBOOK SYNOPSIS:

The two-volume set LNAI 8443 + LNAI 8444 constitutes the refereed proceedings of the 18th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2014, held in Tainan, Taiwan, in May 2014. The 40 full papers and the 60 short papers presented within these proceedings were carefully reviewed and selected from 371 submissions. They cover the general fields of pattern mining; social network and social media; classification; graph and network mining; applications; privacy preserving; recommendation; feature selection and reduction; machine learning; temporal and spatial data; novel algorithms; clustering; biomedical data mining; stream mining; outlier and anomaly detection; multi-sources mining; and unstructured data and text mining.

Data Mining In Large Sets Of Complex Data
Author: Robson Leonardo Ferreira Cordeiro
Publisher: Springer Science & Business Media
Release Date: 2013-01-11
Pages: 116
ISBN:
Available Language: English, Spanish, And French
EBOOK SYNOPSIS:

The amount and the complexity of the data gathered by current enterprises are increasing at an exponential rate. Consequently, the analysis of Big Data is nowadays a central challenge in Computer Science, especially for complex data. For example, given a satellite image database containing tens of Terabytes, how can we find regions aiming at identifying native rainforests, deforestation or reforestation? Can it be made automatically? Based on the work discussed in this book, the answers to both questions are a sound “yes”, and the results can be obtained in just minutes. In fact, results that used to require days or weeks of hard work from human specialists can now be obtained in minutes with high precision. Data Mining in Large Sets of Complex Data discusses new algorithms that take steps forward from traditional data mining (especially for clustering) by considering large, complex datasets. Usually, other works focus in one aspect, either data size or complexity. This work considers both: it enables mining complex data from high impact applications, such as breast cancer diagnosis, region classification in satellite images, assistance to climate change forecast, recommendation systems for the Web and social networks; the data are large in the Terabyte-scale, not in Giga as usual; and very accurate results are found in just minutes. Thus, it provides a crucial and well timed contribution for allowing the creation of real time applications that deal with Big Data of high complexity in which mining on the fly can make an immeasurable difference, such as supporting cancer diagnosis or detecting deforestation.

Mathematical And Physical Fundamentals Of Climate Change
Author: Zhihua Zhang
Publisher: Elsevier
Release Date: 2014-12-06
Pages: 494
ISBN:
Available Language: English, Spanish, And French
EBOOK SYNOPSIS:

Mathematical and Physical Fundamentals of Climate Change is the first book to provide an overview of the math and physics necessary for scientists to understand and apply atmospheric and oceanic models to climate research. The book begins with basic mathematics then leads on to specific applications in atmospheric and ocean dynamics, such as fluid dynamics, atmospheric dynamics, oceanic dynamics, and glaciers and sea level rise. Mathematical and Physical Fundamentals of Climate Change provides a solid foundation in math and physics with which to understand global warming, natural climate variations, and climate models. This book informs the future users of climate models and the decision-makers of tomorrow by providing the depth they need. Developed from a course that the authors teach at Beijing Normal University, the material has been extensively class-tested and contains online resources, such as presentation files, lecture notes, solutions to problems and MATLab codes. Includes MatLab and Fortran programs that allow readers to create their own models Provides case studies to show how the math is applied to climate research Online resources include presentation files, lecture notes, and solutions to problems in book for use in classroom or self-study

Big Data In Ecology
Author:
Publisher: Academic Press
Release Date: 2014-12-01
Pages: 140
ISBN:
Available Language: English, Spanish, And French
EBOOK SYNOPSIS:

The theme of this volume is big data in ecology. Updates and informs the reader on the latest research findings Written by leading experts in the field Highlights areas for future investigation

Broadband Networks  Smart Grids And Climate Change
Author: Eli M. Noam
Publisher: Springer Science & Business Media
Release Date: 2012-12-05
Pages: 258
ISBN:
Available Language: English, Spanish, And French
EBOOK SYNOPSIS:

In smart grids the formerly separated worlds of energy and telecommunication converge to an interactive and automated energy supply system. Driven by social, legal, and economic pressures, energy systems around the globe are updated with information and communication technology. These investments aim at enhancing energy efficiency, securing affordable energy supply, and mitigate climate change. In Broadband Networks, Smart Grids and Climate Change, renowned scholars and managers from the fields of energy and telecommunication address key questions related to technological, strategic, and regulatory issues revealing consequences and opportunities for businesses evolving with smart grids. In particular, this book analyzes: (1) the effects on climate change protection (2) national energy and broadband politics (3) regulatory approaches and requirements (4) emerging business models

Integrated Information And Computing Systems For Natural  Spatial  And Social Sciences
Author: Rückemann, Claus-Peter
Publisher: IGI Global
Release Date: 2012-10-31
Pages: 543
ISBN:
Available Language: English, Spanish, And French
EBOOK SYNOPSIS:

The 21st century has seen a number of advancements in technology, including the use of high performance computing. Computing resources are being used by the science and economy fields for data processing, simulation, and modeling. These innovations aid in the support of production, logistics, and mobility processes. Integrated Information and Computing Systems for Natural, Spatial, and Social Sciences covers a carefully selected spectrum of the most up to date issues, revealing the benefits, dynamism, potential, and challenges of information and computing system application scenarios and components from a wide spectrum of prominent disciplines. This comprehensive collection offers important guidance on the development stage of the universal solution to information and computing systems for researchers as well as industry decision makers and developers.

The Oxford Handbook Of Organizational Climate And Culture
Author: Karen M. Barbera
Publisher: Oxford University Press
Release Date: 2014-05-07
Pages: 752
ISBN:
Available Language: English, Spanish, And French
EBOOK SYNOPSIS:

The Oxford Handbook of Organizational Climate and Culture presents the breadth of topics from Industrial and Organizational Psychology and Organizational Behavior through the lenses of organizational climate and culture. The Handbook reveals in great detail how in both research and practice climate and culture reciprocally influence each other. The details reveal the many practices that organizations use to acquire, develop, manage, motivate, lead, and treat employees both at home and in the multinational settings that characterize contemporary organizations. Chapter authors are both expert in their fields of research and also represent current climate and culture practice in five national and international companies (3M, McDonald's, the Mayo Clinic, PepsiCo and Tata). In addition, new approaches to the collection and analysis of climate and culture data are presented as well as new thinking about organizational change from an integrated climate and culture paradigm. No other compendium integrates climate and culture thinking like this Handbook does and no other compendium presents both an up-to-date review of the theory and research on the many facets of climate and culture as well as contemporary practice. The Handbook takes a climate and culture vantage point on micro approaches to human issues at work (recruitment and hiring, training and performance management, motivation and fairness) as well as organizational processes (teams, leadership, careers, communication), and it also explicates the fact that these are lodged within firms that function in larger national and international contexts.

Big Data  Data Mining  And Machine Learning
Author: Jared Dean
Publisher: John Wiley & Sons
Release Date: 2014-05-07
Pages: 288
ISBN:
Available Language: English, Spanish, And French
EBOOK SYNOPSIS:

With big data analytics comes big insights into profitability Big data is big business. But having the data and the computational power to process it isn't nearly enough to produce meaningful results. Big Data, Data Mining, and Machine Learning: Value Creation for Business Leaders and Practitioners is a complete resource for technology and marketing executives looking to cut through the hype and produce real results that hit the bottom line. Providing an engaging, thorough overview of the current state of big data analytics and the growing trend toward high performance computing architectures, the book is a detail-driven look into how big data analytics can be leveraged to foster positive change and drive efficiency. With continued exponential growth in data and ever more competitive markets, businesses must adapt quickly to gain every competitive advantage available. Big data analytics can serve as the linchpin for initiatives that drive business, but only if the underlying technology and analysis is fully understood and appreciated by engaged stakeholders. This book provides a view into the topic that executives, managers, and practitioners require, and includes: A complete overview of big data and its notable characteristics Details on high performance computing architectures for analytics, massively parallel processing (MPP), and in-memory databases Comprehensive coverage of data mining, text analytics, and machine learning algorithms A discussion of explanatory and predictive modeling, and how they can be applied to decision-making processes Big Data, Data Mining, and Machine Learning provides technology and marketing executives with the complete resource that has been notably absent from the veritable libraries of published books on the topic. Take control of your organization's big data analytics to produce real results with a resource that is comprehensive in scope and light on hyperbole.

Big Data In Engineering Applications
Author: Sanjiban Sekhar Roy
Publisher: Springer
Release Date: 2018-05-02
Pages: 384
ISBN:
Available Language: English, Spanish, And French
EBOOK SYNOPSIS:

This book presents the current trends, technologies, and challenges in Big Data in the diversified field of engineering and sciences. It covers the applications of Big Data ranging from conventional fields of mechanical engineering, civil engineering to electronics, electrical, and computer science to areas in pharmaceutical and biological sciences. This book consists of contributions from various authors from all sectors of academia and industries, demonstrating the imperative application of Big Data for the decision-making process in sectors where the volume, variety, and velocity of information keep increasing. The book is a useful reference for graduate students, researchers and scientists interested in exploring the potential of Big Data in the application of engineering areas.

Big Data In Cardiology  Predicting  Preventing And Managing Diseases
Author: Bikal Dhungel
Publisher: GRIN Verlag
Release Date: 2020-10-28
Pages: 59
ISBN:
Available Language: English, Spanish, And French
EBOOK SYNOPSIS:

Master's Thesis from the year 2020 in the subject Health - Health Sciences - Health Logistics, grade: 1,7, Linnaeus University (School of Informatics), course: Information Systems, language: English, abstract: This study was conducted to analyze this process closer focusing on a case of Cardiology. Conducting a comprehensive literature review and qualitative expert interviews, the impact of big data in the field of Cardiology was explored. The result of the study shows that big data can play a positive role in three aspects: prediction of disease, prevention of disease and management of disease. Big data enables us to build models that can be used to predict the occurrence of disease. Based on this information, actions can be taken to prevent the disease. Data also helps to manage the disease by offering helpful insights. Medical personnel can retrieve the patient data, with the help of AI, they can make faster decisions allowing them to spend more quality time with the patients and reduce cognitive errors. Through the interviews, it was understood that even though the positive role of big data has been acknowledged, the implementation is still a challenge due to various limitations. The challenges lie mainly on technical know-how and domain knowledge. Further challenges were data security and privacy issues that need to be addressed to mitigate the risks that can be caused by them. The examples of big data implementation in various cases like in heart failure prediction or prevention shows a positive picture. The overwhelming majority of case studies analyzed in this regard show an optimistic picture. Due to growing importance and use of smart devices, IoT, genomics and the recent developments in the field of ICTs, it is expected that big data will not only leave a positive influence on the field of Cardiology, it will also change the way medicine is practiced and healthcare is offered. The statement ‘Data is the new oil’ has been broadly acknowledged due to its wide-ranging importance. Utilizing big data offers a variety of benefits. Although the health sector was late in terms of exploiting the benefits of big data, currently, the adoption is accelerating. Healthcare is increasingly becoming an information science and the implementation of electronic medical records (EMR) and other information systems is growing rapidly. The patient data originating from smart devices and other sources like genomic databases are supporting the healthcare sector offering better healthcare delivery and increasing efficiency, hence saving costs.

Large Scale Machine Learning In The Earth Sciences
Author: Ashok N. Srivastava
Publisher: CRC Press
Release Date: 2017-08-01
Pages: 208
ISBN:
Available Language: English, Spanish, And French
EBOOK SYNOPSIS:

From the Foreword: "While large-scale machine learning and data mining have greatly impacted a range of commercial applications, their use in the field of Earth sciences is still in the early stages. This book, edited by Ashok Srivastava, Ramakrishna Nemani, and Karsten Steinhaeuser, serves as an outstanding resource for anyone interested in the opportunities and challenges for the machine learning community in analyzing these data sets to answer questions of urgent societal interest...I hope that this book will inspire more computer scientists to focus on environmental applications, and Earth scientists to seek collaborations with researchers in machine learning and data mining to advance the frontiers in Earth sciences." --Vipin Kumar, University of Minnesota Large-Scale Machine Learning in the Earth Sciences provides researchers and practitioners with a broad overview of some of the key challenges in the intersection of Earth science, computer science, statistics, and related fields. It explores a wide range of topics and provides a compilation of recent research in the application of machine learning in the field of Earth Science. Making predictions based on observational data is a theme of the book, and the book includes chapters on the use of network science to understand and discover teleconnections in extreme climate and weather events, as well as using structured estimation in high dimensions. The use of ensemble machine learning models to combine predictions of global climate models using information from spatial and temporal patterns is also explored. The second part of the book features a discussion on statistical downscaling in climate with state-of-the-art scalable machine learning, as well as an overview of methods to understand and predict the proliferation of biological species due to changes in environmental conditions. The problem of using large-scale machine learning to study the formation of tornadoes is also explored in depth. The last part of the book covers the use of deep learning algorithms to classify images that have very high resolution, as well as the unmixing of spectral signals in remote sensing images of land cover. The authors also apply long-tail distributions to geoscience resources, in the final chapter of the book.

Intelligent And Fuzzy Techniques In Big Data Analytics And Decision Making
Author: Cengiz Kahraman
Publisher: Springer
Release Date: 2019-07-05
Pages: 1392
ISBN:
Available Language: English, Spanish, And French
EBOOK SYNOPSIS:

This book includes the proceedings of the Intelligent and Fuzzy Techniques INFUS 2019 Conference, held in Istanbul, Turkey, on July 23–25, 2019. Big data analytics refers to the strategy of analyzing large volumes of data, or big data, gathered from a wide variety of sources, including social networks, videos, digital images, sensors, and sales transaction records. Big data analytics allows data scientists and various other users to evaluate large volumes of transaction data and other data sources that traditional business systems would be unable to tackle. Data-driven and knowledge-driven approaches and techniques have been widely used in intelligent decision-making, and they are increasingly attracting attention due to their importance and effectiveness in addressing uncertainty and incompleteness. INFUS 2019 focused on intelligent and fuzzy systems with applications in big data analytics and decision-making, providing an international forum that brought together those actively involved in areas of interest to data science and knowledge engineering. These proceeding feature about 150 peer-reviewed papers from countries such as China, Iran, Turkey, Malaysia, India, USA, Spain, France, Poland, Mexico, Bulgaria, Algeria, Pakistan, Australia, Lebanon, and Czech Republic.

Data Mining And Knowledge Discovery Handbook
Author: Oded Maimon
Publisher: Springer Science & Business Media
Release Date: 2006-05-28
Pages: 1383
ISBN:
Available Language: English, Spanish, And French
EBOOK SYNOPSIS:

Data Mining and Knowledge Discovery Handbook organizes all major concepts, theories, methodologies, trends, challenges and applications of data mining (DM) and knowledge discovery in databases (KDD) into a coherent and unified repository. This book first surveys, then provides comprehensive yet concise algorithmic descriptions of methods, including classic methods plus the extensions and novel methods developed recently. This volume concludes with in-depth descriptions of data mining applications in various interdisciplinary industries including finance, marketing, medicine, biology, engineering, telecommunications, software, and security. Data Mining and Knowledge Discovery Handbook is designed for research scientists and graduate-level students in computer science and engineering. This book is also suitable for professionals in fields such as computing applications, information systems management, and strategic research management.

Pervasive Cloud Computing Technologies  Future Outlooks And Interdisciplinary Perspectives
Author: Grandinetti, Lucio
Publisher: IGI Global
Release Date: 2013-10-31
Pages: 325
ISBN:
Available Language: English, Spanish, And French
EBOOK SYNOPSIS:

Technology trends may come and go, but cloud computing technologies have been gaining consideration in the commercial world due to its ability to provide on-demand access to resources, control the software environment, and supplement existing systems. Pervasive Cloud Computing Technologies: Future Outlooks and Interdisciplinary Perspectives explores the latest innovations with cloud computing and the impact of these new models and technologies. This book will present case studies and research on the future of cloud computing technologies and its ability to increase connectivity of various entities of the world. It is an essential resource for technology practitioners, engineers, managers, and academics aiming to gain the knowledge of these novel and pervasive technologies.

Social Sensing And Big Data Computing For Disaster Management
Author: Taylor & Francis Group
Publisher: Routledge
Release Date: 2020-11-23
Pages: 183
ISBN:
Available Language: English, Spanish, And French
EBOOK SYNOPSIS:

Social Sensing and Big Data Computing for Disaster Management captures recent advancements in leveraging social sensing and big data computing for supporting disaster management. Specifically, analyzed within this book are some of the promises and pitfalls of social sensing data for disaster relevant information extraction, impact area assessment, population mapping, occurrence patterns, geographical disparities in social media use, and inclusion in larger decision support systems. Traditional data collection methods such as remote sensing and field surveying often fail to offer timely information during or immediately following disaster events. Social sensing enables all citizens to become part of a large sensor network, which is low cost, more comprehensive, and always broadcasting situational awareness information. However, data collected with social sensing is often massive, heterogeneous, noisy, and unreliable from some aspects. It comes in continuous streams, and often lacks geospatial reference information. Together, these issues represent a grand challenge toward fully leveraging social sensing for emergency management decision making under extreme duress. Meanwhile, big data computing methods and technologies such as high-performance computing, deep learning, and multi-source data fusion become critical components of using social sensing to understand the impact of and response to the disaster events in a timely fashion. This book was originally published as a special issue of the International Journal of Digital Earth.

Handbook Of Research On Organizational Transformations Through Big Data Analytics
Author: Tavana, Madjid
Publisher: IGI Global
Release Date: 2014-11-30
Pages: 561
ISBN:
Available Language: English, Spanish, And French
EBOOK SYNOPSIS:

Big data analytics utilizes a wide range of software and analytical tools to provide immediate, relevant information for efficient decision-making. Companies are recognizing the immense potential of BDA, but ensuring the data is appropriate and error-free is the largest hurdle in implementing BDA applications. The Handbook of Research on Organizational Transformations through Big Data Analytics not only catalogues the existing platforms and technologies, it explores new trends within the field of big data analytics (BDA). Containing new and existing research materials and insights on the various approaches to BDA; this publication is intended for researchers, IT professionals, and CIOs interested in the best ways to implement BDA applications and technologies.