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Intelligence Science III - 4th IFIP TC 12 International Conference, ICIS 2020, Durgapur, India, February 24-27, 2021, Revised Selected Papers (Paperback, 1st ed. 2021)
Zhongzhi Shi, Mihir Chakraborty, Samarjit Kar
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R1,569
Discovery Miles 15 690
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Ships in 10 - 15 working days
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This book constitutes the refereed post-conference proceedings of
the 4th International Conference on Intelligence Science, ICIS
2020, held in Durgapur, India, in February 2021 (originally
November 2020). The 23 full papers and 4 short papers presented
were carefully reviewed and selected from 42 submissions. One
extended abstract is also included. They deal with key issues in
brain cognition; uncertain theory; machine learning; data
intelligence; language cognition; vision cognition; perceptual
intelligence; intelligent robot; and medical artificial
intelligence.
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Intelligence Science III - 4th IFIP TC 12 International Conference, ICIS 2020, Durgapur, India, February 24-27, 2021, Revised Selected Papers (Hardcover, 1st ed. 2021)
Zhongzhi Shi, Mihir Chakraborty, Samarjit Kar
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R1,601
Discovery Miles 16 010
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Ships in 10 - 15 working days
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This book constitutes the refereed post-conference proceedings of
the 4th International Conference on Intelligence Science, ICIS
2020, held in Durgapur, India, in February 2021 (originally
November 2020). The 23 full papers and 4 short papers presented
were carefully reviewed and selected from 42 submissions. One
extended abstract is also included. They deal with key issues in
brain cognition; uncertain theory; machine learning; data
intelligence; language cognition; vision cognition; perceptual
intelligence; intelligent robot; and medical artificial
intelligence.
This book discusses recent developments in the vast domain of
optimization. Featuring papers presented at the 1st International
Conference on Frontiers in Optimization: Theory and Applications
(FOTA 2016), held at the Heritage Institute of Technology, Kolkata,
on 24-26 December 2016, it opens new avenues of research in all
topics related to optimization, such as linear and nonlinear
optimization; combinatorial-, stochastic-, dynamic-, fuzzy-, and
uncertain optimization; optimal control theory; as well as
multi-objective, evolutionary and convex optimization and their
applications in intelligent information and technology, systems
science, knowledge management, information and communication,
supply chain and inventory control, scheduling, networks,
transportation and logistics and finance. The book is a valuable
resource for researchers, scientists and engineers from both
academia and industry.
The proceedings of the 4th International Conference on Frontiers in
Intelligent Computing: Theory and Applications 2015 (FICTA 2015)
serves as the knowledge centre not only for scientists and
researchers in the field of intelligent computing but also for
students of post-graduate level in various engineering disciplines.
The book covers a comprehensive overview of the theory, methods,
applications and tools of Intelligent Computing. Researchers are
now working in interdisciplinary areas and the proceedings of FICTA
2015 plays a major role to accumulate those significant works in
one arena. The chapters included in the proceedings inculcates both
theoretical as well as practical aspects of different areas like
Nature Inspired Algorithms, Fuzzy Systems, Data Mining, Signal
Processing, Image processing, Text Processing, Wireless Sensor
Networks, Network Security and Cellular Automata.
Since the emergence of the formal concept of probability theory in
the seventeenth century, uncertainty has been perceived solely in
terms of probability theory. However, this apparently unique link
between uncertainty and probability theory has come under
investigation a few decades back. Uncertainties are nowadays
accepted to be of various kinds. Uncertainty in general could refer
to different sense like not certainly known, questionable,
problematic, vague, not definite or determined, ambiguous, liable
to change, not reliable. In Indian languages, particularly in
Sanskrit-based languages, there are other higher levels of
uncertainties. It has been shown that several mathematical concepts
such as the theory of fuzzy sets, theory of rough sets, evidence
theory, possibility theory, theory of complex systems and complex
network, theory of fuzzy measures and uncertainty theory can also
successfully model uncertainty.
Effective decision-making while trading off the constraints and
conflicting multiple objectives under rapid technological
developments, massive generation of data, and extreme volatility is
of paramount importance to organizations to win over the time-based
competition today. While agility is a crucial issue, the firms have
been increasingly relying on evidence-based decision-making through
intelligent decision support systems driven by computational
intelligence and automation to achieve a competitive
advantage. The decisions are no longer confined to a
specific functional area. Instead, business organizations today
find actionable insight for formulating future courses of action by
integrating multiple objectives and perspectives. Therefore,
multi-objective decision-making plays a critical role in businesses
and industries. In this regard, the importance of Operations
Research (OR) models and their applications enables the firms to
derive optimum solutions subject to various
constraints and/or objectives while considering multiple
functional areas of the organizations together. Hence, researchers
and practitioners have extensively applied OR models to solve
various organizational issues related to manufacturing, service,
supply chain and logistics management, human resource management,
finance, and market analysis, among others. Further, OR models
driven by AI have been enabled to provide intelligent
decision-support frameworks for achieving sustainable development
goals. The present issue provides a unique platform to showcase the
contributions of the leading international experts on production
systems and business from academia, industry, and government to
discuss the issues in intelligent manufacturing, operations
management, financial management, supply chain management, and
Industry 4.0 in the Artificial Intelligence era. Some of the
general (but not specific) scopes of this proceeding entail OR
models such as Optimization and Control, Combinatorial
Optimization, Queuing Theory, Resource Allocation Models, Linear
and Nonlinear Programming Models, Multi-objective and
multi-attribute Decision Models, Statistical Quality Control along
with AI, Bayesian Data Analysis, Machine Learning and Econometrics
and their applications vis-Ã -vis AI & Data-driven
Production Management, Marketing and Retail Management, Financial
Management, Human Resource Management, Operations Management, Smart
Manufacturing & Industry 4.0, Supply Chain and Logistics
Management, Digital Supply Network, Healthcare Administration,
Inventory Management, consumer behavior, security analysis, and
portfolio management and sustainability. Â The present issue
shall be of interest to the faculty members, students, and scholars
of various engineering and social science institutions and
universities, along with the practitioners and policymakers of
different industries and organizations.
The text book is intended for the undergraduate courses in
mathematics. The utmost care has been taken to ensure that all the
essential topics in Number Theory are adequately emphasized. It
helps the students to assimilate the fundamental concepts to
advanced level theories and the techniques for solving different
types of problems. The example driven approach will help readers in
understanding and applying the concepts of Number Theory through
clear and precise explanations and thoughtfully chosen solved
problems. Key Features This book provides a balanced and
comprehensive coverage of all topics essential to master the
subject at the UG level. Flexible in format, this book explains
concepts clearly and logically with an abundance of examples and
illustrations. It promotes in-depth understanding of the subject
rather than rote memorization.
One of the most appealing and prominent features of operations
research is its inherent interdisciplinary nature. Operations
researchers commonly draw from a wide variety of disciplines
including engineering, economics, computer science, statistics,
psychology and other social and behavioural sciences. Applications
are commonly found in finance, marketing, engineering, accounting,
information systems, politics, medicine, and production/operations
management. Though the development of operations research
consisting more or less of mathematical theories and algorithms,
during last few years some remarkable changes have been shown in
this discipline in connection with recent technological advances
and the increasing scarcity of resources. This volume presents a
number of papers involving theoretical article, use of different
optimization methodologies, and use of metaheuristics algorithms to
solve large complex problems and different application issues.
Most of the real world problems arising in engineering, economics,
management, finance, medicine and other domains can be formulated
as optimization tasks. These problems are frequently characterized
by non-convex, non-differentiable, discontinuous, noisy or dynamic
objective functions and constraints which ask for adequate
computational methods. The aim of this book is to stimulate the
communication between researchers from different fields of
optimization and practitioners who need reliable and efficient
computational optimization methods. This volume presents a number
of papers written by experts in the field of optimization. The
papers involve theoretical articles, optimization methodologies,
evolutionary optimization procedures and application issues. Anyone
interested from the respective fields will find this book extremely
useful.
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