Granular Computing And Big Data Advancements

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Granular Computing And Big Data Advancements

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Author : Zhang, Chao
language : en
Publisher: IGI Global
Release Date : 2024-08-06

Granular Computing And Big Data Advancements written by Zhang, Chao and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-06 with Computers categories.

In an era defined by the deluge of data, navigating the complexities of decision-making under conditions of uncertainty has emerged as a formidable challenge for scholars and practitioners alike. The sheer volume and velocity of information inundating decision-makers often leads to paralysis or misguided choices, amplifying the risks inherent in uncertain environments. Granular Computing and Big Data Advancements provides insights and solutions in this challenging landscape. The impact of Granular Computing and Big Data Advancements reverberates across the research community, offering a cohesive resource that bridges the gap between theory and practice. With its interdisciplinary approach and emphasis on innovation, the book fosters collaboration and empowers scholars to tackle complex challenges head-on. Whether researchers seek novel methodologies, practitioners aim to enhance decision-making processes, or students embark on their academic journey, this publication serves as a cornerstone in the quest for effective decision-making amidst the uncertainties of the modern world.

New Trends In Intelligent Software Methodologies Tools And Techniques

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Author : Hamido Fujita
language : en
Publisher: SAGE Publications Limited
Release Date : 2018-09-15

New Trends In Intelligent Software Methodologies Tools And Techniques written by Hamido Fujita and has been published by SAGE Publications Limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-15 with Computers categories.

Knowledge-based systems, fully integrated with software, have become essential enablers for both science and commerce. But current software methodologies, tools and techniques are not robust or reliable enough for the demands of a constantly changing and evolving market, and many promising approaches have proved to be no more than case-oriented methods that are not fully automated. This book presents the proceedings of the 17th international conference on New Trends in Intelligent Software Methodology, Tools and Techniques (SoMeT18) held in Granada, Spain, 26-28 September 2018. The SoMeT conferences provide a forum for the exchange of ideas and experience, foster new directions in software development methodologies and related tools and techniques, and focus on exploring innovations, controversies, and the current challenges facing the software engineering community. The 80 selected papers included here are divided into 13 chapters, and cover subjects as diverse as intelligent software systems; medical informatics and bioinformatics; artificial intelligence techniques; social learning software and sentiment analysis; cognitive systems and neural analytics; and security, among other things. Offering a state-of-the-art overview of methodologies, tools and techniques, this book will be of interest to all those whose work involves the development or application of software.

Securing Iot And Big Data

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Author : Vijayalakshmi Saravanan
language : en
Publisher: CRC Press
Release Date : 2020-12-16

Securing Iot And Big Data written by Vijayalakshmi Saravanan and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-16 with Computers categories.

This book covers IoT and Big Data from a technical and business point of view. The book explains the design principles, algorithms, technical knowledge, and marketing for IoT systems. It emphasizes applications of big data and IoT. It includes scientific algorithms and key techniques for fusion of both areas. Real case applications from different industries are offering to facilitate ease of understanding the approach. The book goes on to address the significance of security algorithms in combing IoT and big data which is currently evolving in communication technologies. The book is written for researchers, professionals, and academicians from interdisciplinary and transdisciplinary areas. The readers will get an opportunity to know the conceptual ideas with step-by-step pragmatic examples which makes ease of understanding no matter the level of the reader.

Computational Intelligence In Sustainable Computing And Optimization

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Author : Balamurugan Balusamy
language : en
Publisher: Elsevier
Release Date : 2024-10-08

Computational Intelligence In Sustainable Computing And Optimization written by Balamurugan Balusamy and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-08 with Computers categories.

Computational Intelligence in Sustainable Computing and Optimization: Trends and Applications focuses on developing and evolving advanced computational intelligence algorithms for the analysis of data involved in applications, such as agriculture, biomedical systems, bioinformatics, business intelligence, economics, disaster management, e-learning, education management, financial management, and environmental policies. The book presents research in sustainable computing and optimization, combining methods from engineering, mathematics, artificial intelligence, and computer science to optimize environmental resourcesComputational intelligence in the field of sustainable computing combines computer science and engineering in applications ranging from Internet of Things (IoT), information security systems, smart storage, cloud computing, intelligent transport management, cognitive and bio-inspired computing, and management science. In addition, data intelligence techniques play a critical role in sustainable computing. Recent advances in data management, data modeling, data analysis, and artificial intelligence are finding applications in energy networks and thus making our environment more sustainable. - Presents computational, intelligence–based data analysis for sustainable computing applications such as pattern recognition, biomedical imaging, sustainable cities, sustainable transport, sustainable agriculture, and sustainable financial management - Develops research in sustainable computing and optimization, combining methods from engineering, mathematics, and computer science to optimize environmental resources - Includes three foundational chapters dedicated to providing an overview of computational intelligence and optimization techniques and their applications for sustainable computing

Information Granularity Big Data And Computational Intelligence

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Author : Witold Pedrycz
language : en
Publisher: Springer
Release Date : 2014-07-14

Information Granularity Big Data And Computational Intelligence written by Witold Pedrycz and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-07-14 with Technology & Engineering categories.

The recent pursuits emerging in the realm of big data processing, interpretation, collection and organization have emerged in numerous sectors including business, industry and government organizations. Data sets such as customer transactions for a mega-retailer, weather monitoring, intelligence gathering, quickly outpace the capacities of traditional techniques and tools of data analysis. The 3V (volume, variability and velocity) challenges led to the emergence of new techniques and tools in data visualization, acquisition, and serialization. Soft Computing being regarded as a plethora of technologies of fuzzy sets (or Granular Computing), neurocomputing and evolutionary optimization brings forward a number of unique features that might be instrumental to the development of concepts and algorithms to deal with big data. This carefully edited volume provides the reader with an updated, in-depth material on the emerging principles, conceptual underpinnings, algorithms and practice of Computational Intelligence in the realization of concepts and implementation of big data architectures, analysis, and interpretation as well as data analytics. The book is aimed at a broad audience of researchers and practitioners including those active in various disciplines in which big data, their analysis and optimization are of genuine relevance. One focal point is the systematic exposure of the concepts, design methodology, and detailed algorithms. In general, the volume adheres to the top-down strategy starting with the concepts and motivation and then proceeding with the detailed design that materializes in specific algorithms and representative applications. The material is self-contained and provides the reader with all necessary prerequisites and augments some parts with a step-by-step explanation of more advanced concepts supported by a significant amount of illustrative numeric material and some application scenarios to motivate the reader and make some abstract concepts more tangible.

Big Data Quantification For Complex Decision Making

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Author : Chao Zhang
language : en
Publisher:
Release Date : 2024-04-16

Big Data Quantification For Complex Decision Making written by Chao Zhang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-16 with Business & Economics categories.

Many professionals are facing a monumental challenge: navigating the intricate landscape of information to make impactful choices. The sheer volume and complexity of big data have ushered in a shift, demanding innovative methodologies and frameworks. Big Data Quantification for Complex Decision-Making tackles this challenge head-on, offering a comprehensive exploration of the tools necessary to distill valuable insights from datasets. This book serves as a tool for professionals, researchers, and students, empowering them to not only comprehend the significance of big data in decision-making but also to translate this understanding into real-world decision making. The central objective of the book is to examine the relationship between big data and decision-making. It strives to address multiple objectives, including understanding the intricacies of big data in decision-making, navigating methodological nuances, managing uncertainty adeptly, and bridging theoretical foundations with real-world applications. The book's core aspiration is to provide readers with a comprehensive toolbox, seamlessly integrating theoretical frameworks, practical applications, and forward-thinking perspectives. This equips readers with the means to effectively navigate the data-rich landscape of modern decision-making, fostering a heightened comprehension of strategic big data utilization. Tailored for a diverse audience, this book caters to researchers and academics in data science, decision science, machine learning, artificial intelligence, and related domains.

Granular Computing At The Junction Of Rough Sets And Fuzzy Sets

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Author : Rafael Bello
language : en
Publisher: Springer
Release Date : 2007-12-23

Granular Computing At The Junction Of Rough Sets And Fuzzy Sets written by Rafael Bello and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-12-23 with Technology & Engineering categories.

Since their very inception, both fuzzy and rough set theories have earned a sound, well-deserved reputation owing to their intrinsic capabilities to model uncertainty coming from the real world. The increasing amount of investigations on both subjects reported every year in the literature vouches for the dynamics of the area and its rapid advancements. In the last few years the widespread utilization of fuzzy and rough sets as granulation sources has contributed to lay both methodologies in a privileged position within Granular Computing, thus giving rise to a sort a modeling which is far closer to the way human beings perceive their environment – via granulated knowledge. This volume is a compilation of the best papers presented at the First International Symposium on Fuzzy and Rough Sets (ISFUROS 2006) held in Santa Clara, Cuba. You will therefore find valuable contributions both in the theoretical field as in several application domains such as intelligent control, data analysis, decision making and machine learning, just to name a few. Together, they will catch you up with the huge potential of the aforementioned methodologies.

Ensuring Data Integrity In Sensor Based Networked Systems

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Author : Farinaz Koushanfar
language : en
Publisher:
Release Date : 2005

Ensuring Data Integrity In Sensor Based Networked Systems written by Farinaz Koushanfar and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with categories.

Rough Granular Computing In Knowledge Discovery And Data Mining

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Author : J. Stepaniuk
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-08-19

Rough Granular Computing In Knowledge Discovery And Data Mining written by J. Stepaniuk 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 2008-08-19 with Computers categories.

This book covers methods based on a combination of granular computing, rough sets, and knowledge discovery in data mining (KDD). The discussion of KDD foundations based on the rough set approach and granular computing feature illustrative applications.

Big Data Computing

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Author : Tanvir Habib Sardar
language : en
Publisher: CRC Press
Release Date : 2024-02-27

Big Data Computing written by Tanvir Habib Sardar and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-27 with Computers categories.

This book primarily aims to provide an in-depth understanding of recent advances in big data computing technologies, methodologies, and applications along with introductory details of big data computing models such as Apache Hadoop, MapReduce, Hive, Pig, Mahout in-memory storage systems, NoSQL databases, and big data streaming services such as Apache Spark, Kafka, and so forth. It also covers developments in big data computing applications such as machine learning, deep learning, graph processing, and many others. Features: Provides comprehensive analysis of advanced aspects of big data challenges and enabling technologies. Explains computing models using real-world examples and dataset-based experiments. Includes case studies, quality diagrams, and demonstrations in each chapter. Describes modifications and optimization of existing technologies along with the novel big data computing models. Explores references to machine learning, deep learning, and graph processing. This book is aimed at graduate students and researchers in high-performance computing, data mining, knowledge discovery, and distributed computing.