|
Showing 1 - 7 of
7 matches in All Departments
This book collects different methodologies that permit
metaheuristics and machine learning to solve real-world problems.
This book has exciting chapters that employ evolutionary and swarm
optimization tools combined with machine learning techniques. The
fields of applications are from distribution systems until medical
diagnosis, and they are also included different surveys and
literature reviews that will enrich the reader. Besides,
cutting-edge methods such as neuroevolutionary and IoT
implementations are presented in some chapters. In this sense, the
book provides theory and practical content with novel machine
learning and metaheuristic algorithms. The chapters were compiled
using a scientific perspective. Accordingly, the book is primarily
intended for undergraduate and postgraduate students of Science,
Engineering, and Computational Mathematics and can be used in
courses on Artificial Intelligence, Advanced Machine Learning,
among others. Likewise, the material can be helpful for research
from the evolutionary computation, artificial intelligence
communities.
Swarm Intelligence in Cloud Computing is an invaluable treatise for
researchers involved in delivering intelligent optimized solutions
for reliable deployment, infrastructural stability, and security
issues of cloud-based resources. Starting with a bird's eye view on
the prevalent state-of-the-art techniques, this book enriches the
readers with the knowledge of evolving swarm intelligent optimized
techniques for addressing different cloud computing issues
including task scheduling, virtual machine allocation, load
balancing and optimization, deadline handling, power-aware
profiling, fault resilience, cost-effective design, and energy
efficiency. The book offers comprehensive coverage of the most
essential topics, including: Role of swarm intelligence on cloud
computing services Cloud resource sharing strategies Cloud service
provider selection Dynamic task and resource scheduling Data center
resource management. Indrajit Pan is an Associate Professor in
Information Technology of RCC Institute of Information Technology,
India. He received his PhD from Indian Institute of Engineering
Science and Technology, Shibpur, India. With an academic experience
of 14 years, he has published around 40 research publications in
different international journals, edited books, and conference
proceedings. Mohamed Abd Elaziz is a Lecturer in the Mathematical
Department of Zagazig University, Egypt. He received his PhD from
the same university. He is the author of more than 100 articles.
His research interests include machine learning, signal processing,
image processing, cloud computing, and evolutionary algorithms.
Siddhartha Bhattacharyya is a Professor in Computer Science and
Engineering of Christ University, Bangalore. He received his PhD
from Jadavpur University, India. He has published more than 230
research publications in international journals and conference
proceedings in his 20 years of academic experience.
In light of the rapid rise of new trends and applications in
various natural language processing tasks, this book presents
high-quality research in the field. Each chapter addresses a common
challenge in a theoretical or applied aspect of intelligent natural
language processing related to Arabic language. Many challenges
encountered during the development of the solutions can be resolved
by incorporating language technology and artificial intelligence.
The topics covered include machine translation; speech recognition;
morphological, syntactic, and semantic processing; information
retrieval; text classification; text summarization; sentiment
analysis; ontology construction; Arabizi translation; Arabic
dialects; Arabic lemmatization; and building and evaluating
linguistic resources. This book is a valuable reference for
scientists, researchers, and students from academia and industry
interested in computational linguistics and artificial
intelligence, especially for Arabic linguistics and related areas.
This book presents a study of the most important methods of image
segmentation and how they are extended and improved using
metaheuristic algorithms. The segmentation approaches selected have
been extensively applied to the task of segmentation (especially in
thresholding), and have also been implemented using various
metaheuristics and hybridization techniques leading to a broader
understanding of how image segmentation problems can be solved from
an optimization perspective. The field of image processing is
constantly changing due to the extensive integration of cameras in
devices; for example, smart phones and cars now have embedded
cameras. The images have to be accurately analyzed, and crucial
pre-processing steps, like image segmentation, and artificial
intelligence, including metaheuristics, are applied in the
automatic analysis of digital images. Metaheuristic algorithms have
also been used in various fields of science and technology as the
demand for new methods designed to solve complex optimization
problems increases. This didactic book is primarily intended for
undergraduate and postgraduate students of science, engineering,
and computational mathematics. It is also suitable for courses such
as artificial intelligence, advanced image processing, and
computational intelligence. The material is also useful for
researches in the fields of evolutionary computation, artificial
intelligence, and image processing.
In light of the rapid rise of new trends and applications in
various natural language processing tasks, this book presents
high-quality research in the field. Each chapter addresses a common
challenge in a theoretical or applied aspect of intelligent natural
language processing related to Arabic language. Many challenges
encountered during the development of the solutions can be resolved
by incorporating language technology and artificial intelligence.
The topics covered include machine translation; speech recognition;
morphological, syntactic, and semantic processing; information
retrieval; text classification; text summarization; sentiment
analysis; ontology construction; Arabizi translation; Arabic
dialects; Arabic lemmatization; and building and evaluating
linguistic resources. This book is a valuable reference for
scientists, researchers, and students from academia and industry
interested in computational linguistics and artificial
intelligence, especially for Arabic linguistics and related areas.
This book presents a study of the most important methods of image
segmentation and how they are extended and improved using
metaheuristic algorithms. The segmentation approaches selected have
been extensively applied to the task of segmentation (especially in
thresholding), and have also been implemented using various
metaheuristics and hybridization techniques leading to a broader
understanding of how image segmentation problems can be solved from
an optimization perspective. The field of image processing is
constantly changing due to the extensive integration of cameras in
devices; for example, smart phones and cars now have embedded
cameras. The images have to be accurately analyzed, and crucial
pre-processing steps, like image segmentation, and artificial
intelligence, including metaheuristics, are applied in the
automatic analysis of digital images. Metaheuristic algorithms have
also been used in various fields of science and technology as the
demand for new methods designed to solve complex optimization
problems increases. This didactic book is primarily intended for
undergraduate and postgraduate students of science, engineering,
and computational mathematics. It is also suitable for courses such
as artificial intelligence, advanced image processing, and
computational intelligence. The material is also useful for
researches in the fields of evolutionary computation, artificial
intelligence, and image processing.
Get to grips with key IoT aspects along with modern trends,
architectures, and technologies that support IoT solutions, such as
cloud computing, modern app architecture paradigms, and data
analytics Key Features Understand the big picture of designing
production-grade IoT solutions from an industry expert Get up and
running with the development and designing aspects of the Internet
of Things Solve business problems specific to your domain using
different IoT platforms and technologies Book DescriptionWith the
rising demand for and recent enhancements in IoT, a developer with
sound knowledge of IoT is the need of the hour. This book will help
you design, build, and operate large-scale E2E IoT solutions to
transform your business and products, increase revenue, and reduce
operational costs. Starting with an overview of how IoT
technologies can help you solve your business problems, this book
will be a useful guide to helping you implement end-to-end IoT
solution architecture. You'll learn to select IoT devices;
real-time operating systems; IoT Edge covering Edge location,
software, and hardware; and the best IoT connectivity for your IoT
solution. As you progress, you'll work with IoT device management,
IoT data analytics, IoT platforms, and put these components to work
as part of your IoT solution. You'll also be able to build IoT
backend cloud from scratch by leveraging the modern app
architecture paradigms and cloud-native technologies such as
containers and microservices. Finally, you'll discover best
practices for different operational excellence pillars, including
high availability, resiliency, reliability, security, cost
optimization, and high performance, which should be applied for
large-scale production-grade IoT solutions. By the end of this IoT
book, you'll be confident in designing, building, and operating IoT
solutions. What you will learn Understand the detailed anatomy of
IoT solutions and explore their building blocks Explore IoT
connectivity options and protocols used in designing IoT solutions
Understand the value of IoT platforms in building IoT solutions
Explore real-time operating systems used in microcontrollers
Automate device administration tasks with IoT device management
Master different architecture paradigms and decisions in IoT
solutions Build and gain insights from IoT analytics solutions Get
an overview of IoT solution operational excellence pillars Who this
book is forThis book is for E2E solution architects, systems and
technical architects, and IoT developers looking to design, build,
and operate E2E IoT applications and solutions. Basic knowledge of
cloud computing, software engineering, and distributed system
design will help you get the most out of this book.
|
You may like...
Crooked Seeds
Karen Jennings
Paperback
R354
Discovery Miles 3 540
|