Convergence Of Big Data Technologies And Computational Intelligent Techniques PDF Download

Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Convergence Of Big Data Technologies And Computational Intelligent Techniques PDF full book. Access full book title Convergence Of Big Data Technologies And Computational Intelligent Techniques.

Convergence of Big Data Technologies and Computational Intelligent Techniques

Convergence of Big Data Technologies and Computational Intelligent Techniques
Author: Gupta, Govind P.
Publisher: IGI Global
Total Pages: 256
Release: 2022-09-16
Genre: Computers
ISBN: 1668452669
GET BOOK

Download Convergence of Big Data Technologies and Computational Intelligent Techniques Book in PDF, ePub and Kindle

Advanced computational intelligence techniques have been designed and developed in recent years to cope with various big data challenges and provide fast and efficient analytics that assist in making critical decisions. With the rapid evolution and development of internet-based services and applications, this technology is receiving attention from researchers, industries, and academic communities and requires additional study. Convergence of Big Data Technologies and Computational Intelligent Techniques considers recent advancements in big data and computational intelligence across fields and disciplines and discusses the various opportunities and challenges of adoption. Covering topics such as deep learning, data mining, smart environments, and high-performance computing, this reference work is crucial for computer scientists, engineers, industry professionals, researchers, scholars, practitioners, academicians, instructors, and students.

Deep Learning: Convergence to Big Data Analytics

Deep Learning: Convergence to Big Data Analytics
Author: Murad Khan
Publisher: Springer
Total Pages: 79
Release: 2018-12-30
Genre: Computers
ISBN: 9811334595
GET BOOK

Download Deep Learning: Convergence to Big Data Analytics Book in PDF, ePub and Kindle

This book presents deep learning techniques, concepts, and algorithms to classify and analyze big data. Further, it offers an introductory level understanding of the new programming languages and tools used to analyze big data in real-time, such as Hadoop, SPARK, and GRAPHX. Big data analytics using traditional techniques face various challenges, such as fast, accurate and efficient processing of big data in real-time. In addition, the Internet of Things is progressively increasing in various fields, like smart cities, smart homes, and e-health. As the enormous number of connected devices generate huge amounts of data every day, we need sophisticated algorithms to deal, organize, and classify this data in less processing time and space. Similarly, existing techniques and algorithms for deep learning in big data field have several advantages thanks to the two main branches of the deep learning, i.e. convolution and deep belief networks. This book offers insights into these techniques and applications based on these two types of deep learning. Further, it helps students, researchers, and newcomers understand big data analytics based on deep learning approaches. It also discusses various machine learning techniques in concatenation with the deep learning paradigm to support high-end data processing, data classifications, and real-time data processing issues. The classification and presentation are kept quite simple to help the readers and students grasp the basics concepts of various deep learning paradigms and frameworks. It mainly focuses on theory rather than the mathematical background of the deep learning concepts. The book consists of 5 chapters, beginning with an introductory explanation of big data and deep learning techniques, followed by integration of big data and deep learning techniques and lastly the future directions.

Innovations in Computational Intelligence, Big Data Analytics and Internet of Things

Innovations in Computational Intelligence, Big Data Analytics and Internet of Things
Author: Sam Goundar
Publisher: IAP
Total Pages: 385
Release: 2024-03-01
Genre: Computers
ISBN:
GET BOOK

Download Innovations in Computational Intelligence, Big Data Analytics and Internet of Things Book in PDF, ePub and Kindle

As sensors spread across almost every industry, the internet of things is going to trigger a massive influx of big data. We delve into where IoT will have the biggest impact and what it means for the future of big data analytics. Internet of Things is changing the face of different sectors such as manufacturing, health-care, business, education etc. by completely redefining the way people, devices, and apps connect and interact with each other in the eco system. From personal fitness and wellness sensors, implantable devices to surgical robots – IoT is bringing in new tools and efficiencies in the ecosystem resulting in more integrated healthcare. Application of computational intelligence techniques is today considered as a key success factor to solve the growing scale and complexity of problems in the field of health care systems, agriculture, e-commerce etc. The convergence of Computational intelligence, Big Data and IoT provides new opportunities and revolutionize business in huge way. This book will support industry and governmental agencies to facilitate and make sense of myriad connected devices in coming decade. This book offers the recent advancements in Computational Intelligence, IoT and Big Data Analytics. • Development of models and algorithms for employing IoT based facilities in healthcare, industry, agriculture, e- commerce, manufacturing, business etc. • Methods for collection, management retrieval and processing of Big Data in various domains. • Provides taxonomy of challenges, issues and research directions in applications of computational intelligence techniques in different domains

Convergence of Cloud with AI for Big Data Analytics

Convergence of Cloud with AI for Big Data Analytics
Author: Danda B. Rawat
Publisher: John Wiley & Sons
Total Pages: 452
Release: 2023-02-13
Genre: Computers
ISBN: 1119905214
GET BOOK

Download Convergence of Cloud with AI for Big Data Analytics Book in PDF, ePub and Kindle

CONVERGENCE of CLOUD with AI for BIG DATA ANALYTICS This book covers the foundations and applications of cloud computing, AI, and Big Data and analyses their convergence for improved development and services. The 17 chapters of the book masterfully and comprehensively cover the intertwining concepts of artificial intelligence, cloud computing, and big data, all of which have recently emerged as the next-generation paradigms. There has been rigorous growth in their applications and the hybrid blend of AI Cloud and IoT (Ambient-intelligence technology) also relies on input from wireless devices. Despite the multitude of applications and advancements, there are still some limitations and challenges to overcome, such as security, latency, energy consumption, service allocation, healthcare services, network lifetime, etc. Convergence of Cloud with AI for Big Data Analytics: Foundations and Innovation details all these technologies and how they are related to state-of-the-art applications, and provides a comprehensive overview for readers interested in advanced technologies, identifying the challenges, proposed solutions, as well as how to enhance the framework. Audience Researchers and post-graduate students in computing as well as engineers and practitioners in software engineering, electrical engineers, data analysts, and cyber security professionals.

Convergence of Deep Learning and Internet of Things: Computing and Technology

Convergence of Deep Learning and Internet of Things: Computing and Technology
Author: Kavitha, T.
Publisher: IGI Global
Total Pages: 371
Release: 2022-12-19
Genre: Computers
ISBN: 166846277X
GET BOOK

Download Convergence of Deep Learning and Internet of Things: Computing and Technology Book in PDF, ePub and Kindle

Digital technology has enabled a number of internet-enabled devices that generate huge volumes of data from different systems. This large amount of heterogeneous data requires efficient data collection, processing, and analytical methods. Deep Learning is one of the latest efficient and feasible solutions that enable smart devices to function independently with a decision-making support system. Convergence of Deep Learning and Internet of Things: Computing and Technology contributes to technology and methodology perspectives in the incorporation of deep learning approaches in solving a wide range of issues in the IoT domain to identify, optimize, predict, forecast, and control emerging IoT systems. Covering topics such as data quality, edge computing, and attach detection and prediction, this premier reference source is a comprehensive resource for electricians, communications specialists, mechanical engineers, civil engineers, computer scientists, students and educators of higher education, librarians, researchers, and academicians.

Revolutionizing Industrial Automation Through the Convergence of Artificial Intelligence and the Internet of Things

Revolutionizing Industrial Automation Through the Convergence of Artificial Intelligence and the Internet of Things
Author: Mishra, Divya Upadhyay
Publisher: IGI Global
Total Pages: 298
Release: 2022-09-23
Genre: Computers
ISBN: 1668449935
GET BOOK

Download Revolutionizing Industrial Automation Through the Convergence of Artificial Intelligence and the Internet of Things Book in PDF, ePub and Kindle

With the development of innovative technologies, the study of industrial automation is obtaining extraordinary attention from academia, governments, researchers, and various industrial communities. The technical innovations in advanced technologies such as deep learning, blockchain, artificial intelligence of things (AIOT), and more have unlocked the potential for bringing intelligent automation and efficiency to the industries to control their various operations. These new technologies provide an efficient and secure way for industries to manage and develop products intelligently. Revolutionizing Industrial Automation Through the Convergence of Artificial Intelligence and the Internet of Things includes the recent advancements in exploring and developing AIOT-powered strategies and mechanisms for future industrial automation and transforming industrial functions and architectures to help improve various industrial operations. Covering topics such as convolutional neural networks, smart urban logistics, and industrial automation, this premier reference source is an excellent resource for computer scientists, IT managers, engineers, business leaders and executives, logistics managers, students and faculty of higher education, libraries, researchers, and academicians.

Information Granularity, Big Data, and Computational Intelligence

Information Granularity, Big Data, and Computational Intelligence
Author: Witold Pedrycz
Publisher: Springer
Total Pages: 444
Release: 2014-07-14
Genre: Technology & Engineering
ISBN: 331908254X
GET BOOK

Download Information Granularity, Big Data, and Computational Intelligence Book in PDF, ePub and Kindle

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 Computing

Big Data Computing
Author: Tanvir Habib Sardar
Publisher: CRC Press
Total Pages: 397
Release: 2024-02-27
Genre: Computers
ISBN: 100382272X
GET BOOK

Download Big Data Computing Book in PDF, ePub and Kindle

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.

Computational Intelligence for Big Data Analysis

Computational Intelligence for Big Data Analysis
Author: D.P. Acharjya
Publisher: Springer
Total Pages: 276
Release: 2015-04-21
Genre: Technology & Engineering
ISBN: 3319165984
GET BOOK

Download Computational Intelligence for Big Data Analysis Book in PDF, ePub and Kindle

The work presented in this book is a combination of theoretical advancements of big data analysis, cloud computing, and their potential applications in scientific computing. The theoretical advancements are supported with illustrative examples and its applications in handling real life problems. The applications are mostly undertaken from real life situations. The book discusses major issues pertaining to big data analysis using computational intelligence techniques and some issues of cloud computing. An elaborate bibliography is provided at the end of each chapter. The material in this book includes concepts, figures, graphs, and tables to guide researchers in the area of big data analysis and cloud computing.

Multidisciplinary Applications of Deep Learning-Based Artificial Emotional Intelligence

Multidisciplinary Applications of Deep Learning-Based Artificial Emotional Intelligence
Author: Chowdhary, Chiranji Lal
Publisher: IGI Global
Total Pages: 315
Release: 2022-10-21
Genre: Computers
ISBN: 1668456753
GET BOOK

Download Multidisciplinary Applications of Deep Learning-Based Artificial Emotional Intelligence Book in PDF, ePub and Kindle

Emotional intelligence has emerged as an important area of research in the artificial intelligence field as it covers a wide range of real-life domains. Though machines may never need all the emotional skills that people need, there is evidence to suggest that machines require at least some of these skills to appear intelligent when interacting with people. To understand how deep learning-based emotional intelligence can be applied and utilized across industries, further study on its opportunities and future directions is required. Multidisciplinary Applications of Deep Learning-Based Artificial Emotional Intelligence explores artificial intelligence applications, such as machine and deep learning, in emotional intelligence and examines their use towards attaining emotional intelligence acceleration and augmentation. It provides research on tools used to simplify and streamline the formation of deep learning for system architects and designers. Covering topics such as data analytics, deep learning, knowledge management, and virtual emotional intelligence, this reference work is ideal for computer scientists, engineers, industry professionals, researchers, scholars, practitioners, academicians, instructors, and students.