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Reliability technology plays an important role in the present era
of industrial growth, optimal efficiency, and reducing hazards.
This book provides insights into current advances and developments
in reliability engineering, and the research presented is spread
across all branches. It discusses interdisciplinary solutions to
complex problems using different approaches to save money, time,
and manpower. It presents methodologies of coping with uncertainty
in reliability optimization through the usage of various techniques
such as soft computing, fuzzy optimization, uncertainty, and
maintenance scheduling. Case studies and real-world examples are
presented along with applications that can be used in practice.
This book will be useful to researchers, academicians, and
practitioners working in the area of reliability and systems
assurance engineering. Provides current advances and developments
across different branches of engineering. Reviews and analyses case
studies and real-world examples. Presents applications to be used
in practice. Includes numerous examples to illustrate theoretical
results.
This book presents a collection of recent research on topics
related to Pythagorean fuzzy set, dealing with dynamic and complex
decision-making problems. It discusses a wide range of theoretical
and practical information to the latest research on Pythagorean
fuzzy sets, allowing readers to gain an extensive understanding of
both fundamentals and applications. It aims at solving various
decision-making problems such as medical diagnosis, pattern
recognition, construction problems, technology selection, and more,
under the Pythagorean fuzzy environment, making it of much value to
students, researchers, and professionals associated with the field.
This book presents a collection of recent research on topics
related to Pythagorean fuzzy set, dealing with dynamic and complex
decision-making problems. It discusses a wide range of theoretical
and practical information to the latest research on Pythagorean
fuzzy sets, allowing readers to gain an extensive understanding of
both fundamentals and applications. It aims at solving various
decision-making problems such as medical diagnosis, pattern
recognition, construction problems, technology selection, and more,
under the Pythagorean fuzzy environment, making it of much value to
students, researchers, and professionals associated with the field.
Reliability technology plays an important role in the present era
of industrial growth, optimal efficiency, and reducing hazards.
This book provides insights into current advances and developments
in reliability engineering, and the research presented is spread
across all branches. It discusses interdisciplinary solutions to
complex problems using different approaches to save money, time,
and manpower. It presents methodologies of coping with uncertainty
in reliability optimization through the usage of various techniques
such as soft computing, fuzzy optimization, uncertainty, and
maintenance scheduling. Case studies and real-world examples are
presented along with applications that can be used in practice.
This book will be useful to researchers, academicians, and
practitioners working in the area of reliability and systems
assurance engineering. Provides current advances and developments
across different branches of engineering. Reviews and analyses case
studies and real-world examples. Presents applications to be used
in practice. Includes numerous examples to illustrate theoretical
results.
Deep Learning in Personalized Healthcare and Decision Support
discusses the potential of deep learning technologies in the
healthcare sector. The book covers the application of deep learning
tools and techniques in diverse areas of healthcare, such as
medical image classification, telemedicine, clinical decision
support system, clinical trials, electronic health records,
precision medication, Parkinson disease detection, genomics, and
drug discovery. In addition, it discusses the use of DL for fraud
detection and internet of things. This is a valuable resource for
researchers, graduate students and healthcare professionals who are
interested in learning more about deep learning applied to the
healthcare sector. Although there is an increasing interest by
clinicians and healthcare workers, they still lack enough knowledge
to efficiently choose and make use of technologies currently
available. This book fills that knowledge gap by bringing together
experts from technology and clinical fields to cover the topics in
depth.
This two-volume book gathers the proceedings of the Sixth
International Conference on Soft Computing for Problem Solving
(SocProS 2016), offering a collection of research papers presented
during the conference at Thapar University, Patiala, India.
Providing a veritable treasure trove for scientists and researchers
working in the field of soft computing, it highlights the latest
developments in the broad area of "Computational Intelligence" and
explores both theoretical and practical aspects using fuzzy logic,
artificial neural networks, evolutionary algorithms, swarm
intelligence, soft computing, computational intelligence, etc.
This book collects chapters which discuss interdisciplinary
solutions to complex problems by using different approaches in
order to save money, time and resources. The book presents the
results on the recent advancements in artificial intelligence,
computational intelligence, decision-making problems, emerging
problems and practical achievements in the broad knowledge
management field. q-ROFS is one of the hot topics for all the
researchers, industrialists as well as academicians. This book is
of interest to professionals and researchers working in the field
of decision making and computational intelligence, as well as
postgraduate and undergraduate students studying applications of
fuzzy sets. The book helps solve different kinds of the
decision-making problems such as medical diagnosis, pattern
recognition, construction problems and technology selection under
the uncertain fuzzy environment. Containing 19 chapters, the book
begins by giving a topology of the q-ROFSs and their applications.
It then progresses in a logical fashion, dedicating a chapter to
each approach, including the generalized information measures for
q-ROFSs, implementation of q-ROFSs to medical diagnosis, inventory
model, multi-attribute decision-making and approaches to real-life
industrial problems such as green campus transportation, social
responsibility evaluation pattern and extensions of the q-ROFSs.
Engineering Reliability and Risk Assessment explains how to improve
the performance of a system using the latest risk and reliability
models. Against a backdrop of increasing availability of industrial
data, and ever-increasing global commercial competition, the
standards for optimal efficiency with minimum hazards keep
improving. Topics explained include Effective strategies for the
maintenance of the mechanical components of a system, How to
schedule necessary interventions throughout the product life cycle,
How to understand the structure and cost of complex systems,
Planning a schedule to improve the reliability and life of the
system, software, system safety and risk informed asset management,
and more.
This book introduces readers to the concept of the neutrosophic set
which can deal with dynamic and complex decision-making problems.
With the complexity of the socio-economic environment, todays
decision-making is one of the most notable ventures, whose mission
is to decide the best alternative under numerous known or unknown
criteria. This book provides a large amount of theoretical and
practical information about the latest research in the field,
allowing readers to gain an extensive understanding of both the
fundamentals and applications of neutrosophic sets to solve
different kinds of decision-making problems and mathematical
programming such as medical diagnosis, pattern recognition,
construction problems, technology selection etc.
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