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Applied Machine Learning for Smart Data Analysis

Author: Nilanjan Dey

Publisher: CRC Press

Published: 2019-05-20

Total Pages: 225

ISBN-13: 0429804571

The book focuses on how machine learning and the Internet of Things (IoT) has empowered the advancement of information driven arrangements including key concepts and advancements. Ontologies that are used in heterogeneous IoT environments have been discussed including interpretation, context awareness, analyzing various data sources, machine learning algorithms and intelligent services and applications. Further, it includes unsupervised and semi-supervised machine learning techniques with study of semantic analysis and thorough analysis of reviews. Divided into sections such as machine learning, security, IoT and data mining, the concepts are explained with practical implementation including results. Key Features Follows an algorithmic approach for data analysis in machine learning Introduces machine learning methods in applications Address the emerging issues in computing such as deep learning, machine learning, Internet of Things and data analytics Focuses on machine learning techniques namely unsupervised and semi-supervised for unseen and seen data sets Case studies are covered relating to human health, transportation and Internet applications

Artificial Intelligence and Big Data Analytics for Smart Healthcare

Author: Miltiadis Lytras

Publisher: Academic Press

Published: 2021-10-22

Total Pages: 292

ISBN-13: 0128220627

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Artificial Intelligence and Big Data Analytics for Smart Healthcare serves as a key reference for practitioners and experts involved in healthcare as they strive to enhance the value added of healthcare and develop more sustainable healthcare systems. It brings together insights from emerging sophisticated information and communication technologies such as big data analytics, artificial intelligence, machine learning, data science, medical intelligence, and, by dwelling on their current and prospective applications, highlights managerial and policymaking challenges they may generate. The book is split into five sections: big data infrastructure, framework and design for smart healthcare; signal processing techniques for smart healthcare applications; business analytics (descriptive, diagnostic, predictive and prescriptive) for smart healthcare; emerging tools and techniques for smart healthcare; and challenges (security, privacy, and policy) in big data for smart healthcare. The content is carefully developed to be understandable to different members of healthcare chain to leverage collaborations with researchers and industry. Presents a holistic discussion on the new landscape of data driven medical technologies including Big Data, Analytics, Artificial Intelligence, Machine Learning, and Precision Medicine Discusses such technologies with case study driven approach with reference to real world application and systems, to make easier the understanding to the reader not familiar with them Encompasses an international collaboration perspective, providing understandable knowledge to professionals involved with healthcare to leverage productive partnerships with technology developers

Advanced Information Technology, Services and Systems

Author: Mostafa Ezziyyani

Publisher: Springer

Published: 2017-11-10

Total Pages: 518

ISBN-13: 3319691376

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This book includes the proceedings of the International Conference on Advanced Information Technology, Services and Systems (AIT2S-17) held on April 14–15, 2017 in Tangier, Morocco. Presenting the latest research in the field, it stimulates debate, discusses new challenges and provides insights into the field in order to promote closer interaction and interdisciplinary collaboration between researchers and practitioners. Intended for researchers and practitioners in advanced information technology/management and networking, the book is also of interest to those in emergent fields such as data science and analytics, big data, Internet of Things, smart networked systems, artificial intelligence and expert systems, pattern recognition, and cloud computing.

Computational Intelligence for Multimedia Big Data on the Cloud with Engineering Applications

Author: Arun Kumar Sangaiah

Publisher: Academic Press

Published: 2018-08-21

Total Pages: 362

ISBN-13: 0128133279

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Computational Intelligence for Multimedia Big Data on the Cloud with Engineering Applications covers timely topics, including the neural network (NN), particle swarm optimization (PSO), evolutionary algorithm (GA), fuzzy sets (FS) and rough sets (RS), etc. Furthermore, the book highlights recent research on representative techniques to elaborate how a data-centric system formed a powerful platform for the processing of cloud hosted multimedia big data and how it could be analyzed, processed and characterized by CI. The book also provides a view on how techniques in CI can offer solutions in modeling, relationship pattern recognition, clustering and other problems in bioengineering. It is written for domain experts and developers who want to understand and explore the application of computational intelligence aspects (opportunities and challenges) for design and development of a data-centric system in the context of multimedia cloud, big data era and its related applications, such as smarter healthcare, homeland security, traffic control trading analysis and telecom, etc. Researchers and PhD students exploring the significance of data centric systems in the next paradigm of computing will find this book extremely useful. Presents a brief overview of computational intelligence paradigms and its significant role in application domains Illustrates the state-of-the-art and recent developments in the new theories and applications of CI approaches Familiarizes the reader with computational intelligence concepts and technologies that are successfully used in the implementation of cloud-centric multimedia services in massive data processing Provides new advances in the fields of CI for bio-engineering application

Computational Intelligent Data Analysis for Sustainable Development

Author: Ting Yu

Publisher: CRC Press

Published: 2016-04-19

Total Pages: 443

ISBN-13: 1439895953

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Going beyond performing simple analyses, researchers involved in the highly dynamic field of computational intelligent data analysis design algorithms that solve increasingly complex data problems in changing environments, including economic, environmental, and social data. Computational Intelligent Data Analysis for Sustainable Development present

Smart Data and Computational Intelligence

Author: Faddoul Khoukhi

Publisher: Springer

Published: 2019-02-28

Total Pages: 298

ISBN-13: 3030119149

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This book gathers the proceedings of the International Conference on Advanced Information Technology, Services and Systems (AIT2S-18), which was held in Mohammedia, Morocco on October 17–18, 2018. Presenting the latest research in the fields of Modern Information Engineering Concepts and Communication Systems, the book will also be of interest to those working in emerging fields such as Advances in Networking and Sensor Networks, Advances in Software Engineering, Multimedia Systems, E-learning, Big Data, Intelligent Information Systems and Advances in Natural Language Processing.

Smart Information Systems

Author: Frank Hopfgartner

Publisher: Springer

Published: 2015-01-14

Total Pages: 378

ISBN-13: 3319141783

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This text presents an overview of smart information systems for both the private and public sector, highlighting the research questions that can be studied by applying computational intelligence. The book demonstrates how to transform raw data into effective smart information services, covering the challenges and potential of this approach. Each chapter describes the algorithms, tools, measures and evaluations used to answer important questions. This is then further illustrated by a diverse selection of case studies reflecting genuine problems faced by SMEs, multinational manufacturers, service companies, and the public sector. Features: provides a state-of-the-art introduction to the field, integrating contributions from both academia and industry; reviews novel information aggregation services; discusses personalization and recommendation systems; examines sensor-based knowledge acquisition services, describing how the analysis of sensor data can be used to provide a clear picture of our world.

Applications of Artificial Intelligence for Smart Technology

Author: Swarnalatha, P.

Publisher: IGI Global

Published: 2020-10-30

Total Pages: 330

ISBN-13: 1799833372

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As global communities are attempting to transform into more efficient and technologically-advanced metropolises, artificial intelligence (AI) has taken a firm grasp on various professional fields. Technology used in these industries is transforming by introducing intelligent techniques including machine learning, cognitive computing, and computer vision. This has raised significant attention among researchers and practitioners on the specific impact that these smart technologies have and what challenges remain. Applications of Artificial Intelligence for Smart Technology is a pivotal reference source that provides vital research on the implementation of advanced technological techniques in professional industries through the use of AI. While highlighting topics such as pattern recognition, computational imaging, and machine learning, this publication explores challenges that various fields currently face when applying these technologies and examines the future uses of AI. This book is ideally designed for researchers, developers, managers, academicians, analysts, students, and practitioners seeking current research on the involvement of AI in professional practices.

Machine Intelligence and Data Analytics for Sustainable Future Smart Cities

Author: Uttam Ghosh

Publisher: Springer Nature

Published: 2021-05-31

Total Pages: 411

ISBN-13: 3030720659

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This book presents the latest advances in computational intelligence and data analytics for sustainable future smart cities. It focuses on computational intelligence and data analytics to bring together the smart city and sustainable city endeavors. It also discusses new models, practical solutions and technological advances related to the development and the transformation of cities through machine intelligence and big data models and techniques. This book is helpful for students and researchers as well as practitioners.

Computational Intelligence Techniques for Green Smart Cities

Author: Mohamed Lahby

Publisher: Springer Nature

Published: 2022-04-22

Total Pages: 418

ISBN-13: 3030964299

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This book contains high-quality and original research on computational intelligence for green smart cities research. In recent years, the use of smart city technology has rapidly increased through the successful development and deployment of Internet of Things (IoT) architectures. The citizens' quality of life has been improved in several sensitive areas of the city, such as transportation, buildings, health care, education, environment, and security, thanks to these technological advances Computational intelligence techniques and algorithms enable a computational analysis of enormous data sets to reveal patterns that recur. This information is used to inform and improve decision-making at the municipal level to build smart computational intelligence techniques and sustainable cities for their citizens. Machine intelligence allows us to identify trends (patterns). The smart city could better integrate its transportation network, for example. By offering a better public transportation network adapted to the demand, we could reduce personal vehicles and energy consumption. A smart city could use models to predict the consequences of a change, such as pedestrianizing a street or adding a bike lane. A city can even create a 3D digital twin to test hypothetical projects. This book comprises many state-of-the-art contributions from scientists and practitioners working in machine intelligence and green smart cities. It aspires to provide a relevant reference for students, researchers, engineers, and professionals working in this area or those interested in grasping its diverse facets and exploring the latest advances in machine intelligence for green and sustainable smart city applications.