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Highlights the importance and applications of Swarm Intelligence
and Machine learning in Healthcare industry. Elaborates Swarm
Intelligence and Machine Learning for Cancer Detection. Focuses on
applying Swarm Intelligence and Machine Learning for Heart Disease
detection and diagnosis. Explores of the concepts of machine
learning along with swarm intelligence techniques, along with
recent research developments in healthcare sectors. Investigates
how healthcare companies can leverage the tapestry of big data to
discover new business values. Provides a strong foundation for
Diabetic Retinopathy detection using Swarm and Evolutionary
algorithms.
This book is a collection of peer-reviewed best selected research
papers presented at the First International Conference on Machine
Intelligence and Smart Systems 2020 (MISS 2020), organized during
September 24-25, 2020, in Gwalior, India. The book presents new
advances and research results in the fields of machine
intelligence, artificial intelligence and smart systems. It
includes main paradigms of machine intelligence algorithms, namely
(1) neural networks, (2) evolutionary computation, (3) swarm
intelligence, (4) fuzzy systems and (5) immunological computation.
This book presents a compilation of current trends, technologies,
and challenges in connection with Big Data. Many fields of science
and engineering are data-driven, or generate huge amounts of data
that are ripe for the picking. There are now more sources of data
than ever before, and more means of capturing data. At the same
time, the sheer volume and complexity of the data have sparked new
developments, where many Big Data problems require new solutions.
Given its scope, the book offers a valuable reference guide for all
graduate students, researchers, and scientists interested in
exploring the potential of Big Data applications.
This book presents a compilation of current trends, technologies,
and challenges in connection with Big Data. Many fields of science
and engineering are data-driven, or generate huge amounts of data
that are ripe for the picking. There are now more sources of data
than ever before, and more means of capturing data. At the same
time, the sheer volume and complexity of the data have sparked new
developments, where many Big Data problems require new solutions.
Given its scope, the book offers a valuable reference guide for all
graduate students, researchers, and scientists interested in
exploring the potential of Big Data applications.
The book contains select proceedings of the 3rd International
Conference on Data, Engineering, and Applications (IDEA 2021). It
includes papers from experts in industry and academia that address
state-of-the-art research in the areas of big data, data mining,
machine learning, data science, and their associated learning
systems and applications. This book will be a valuable reference
guide for all graduate students, researchers, and scientists
interested in exploring the potential of big data applications.
This book is a collection of peer-reviewed best selected research
papers presented at the Second International Conference on Machine
Intelligence and Smart Systems (MISS 2021), organized during
September 24-25, 2021, in Gwalior, India. The book presents new
advances and research results in the fields of machine
intelligence, artificial intelligence and smart systems. It
includes main paradigms of machine intelligence algorithms, namely
(1) neural networks, (2) evolutionary computation, (3) swarm
intelligence, (4) fuzzy systems and (5) immunological computation.
Scientists, engineers, academicians, technology developers,
researchers, students and government officials will find this book
useful in handling their complicated real-world issues by using
machine intelligence methodologies.
Association rule mining is the most popular data mining techniques
to find association among items in a set by mining necessary
patterns in a large database, frequently used in marketing,
advertising and inventory control. Typically association rules
consider only items enumerated in transactions, referred as
positive association rules but not consider negative occurrence of
attributes that are also useful in market-basket analysis to
identify products that conflict with each other or products that
complement each other. Also for mining those positive rules that
qualify the user specified threshold criteria, algorithm generates
too many candidate itemsets by scanning database multiple times. In
order to resolve all the bottleneck of association rule mining
algorithm, in this we propose an algorithm SARIC which implements
Set Particle Swarm Optimization heuristic technique for generating
association rules from a database that also consider negative
occurrence of attribute along with positive occurrence. SARIC uses
the concept of IR and Correlation Coefficient and there is no need
to specify minimum support and confidence, it automatically
determines them quickly and objectively
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Data Structures (Paperback)
N.K. Tiwari, Jitendra Agrawal, Shishir K. Shandilya
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R781
Discovery Miles 7 810
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Ships in 12 - 17 working days
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Data structure is a way of organizing data in a computer memory so
that it can be used efficiently. Data structures can implement one
or more particular abstract data types (ADT), which are the means
of specifying the nature of operations and their complexity. This
book focuses on the design and analysis of basic data structures
and their implementation and intends to provide a strong conceptual
and empirical understanding of data structures. The contents of
this book will help the students to understand that how the data
structures are implemented and why these implementations are vital.
The initial chapters deal with introductory part of the subject and
the later chapters focus on advanced and difficult problems and
algorithms. The book explains how data is organized in computer
memory; how it operates; and why it is important. Appendixes
provide further information on algorithms along with their
programming solutions. Readers of this book need only to be
familiar with the basic syntax of C/C++ and similar languages. This
book will be useful for B.Tech/M.Tech Computer Science and
Engineering, IT Engineering, BSc (IT)/MSc (IT), and BCA/MCA
students.
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