Soft Computing Techniques in Engineering, Health, Mathematical and Social Sciences


Book Description

Soft computing techniques are no longer limited to the arena of computer science. The discipline has an exponentially growing demand in other branches of science and engineering and even into health and social science. This book contains theory and applications of soft computing in engineering, health, and social and applied sciences. Different soft computing techniques such as artificial neural networks, fuzzy systems, evolutionary algorithms and hybrid systems are discussed. It also contains important chapters in machine learning and clustering. This book presents a survey of the existing knowledge and also the current state of art development through original new contributions from the researchers. This book may be used as a one-stop reference book for a broad range of readers worldwide interested in soft computing. In each chapter, the preliminaries have been presented first and then the advanced discussion takes place. Learners and researchers from a wide variety of backgrounds will find several useful tools and techniques to develop their soft computing skills. This book is meant for graduate students, faculty and researchers willing to expand their knowledge in any branch of soft computing. The readers of this book will require minimum prerequisites of undergraduate studies in computation and mathematics.




Soft Computing


Book Description

This book examines the latest developments in the area of soft computing with engineering applications. It explores topics such as fuzzy sets, intuitionistic fuzzy sets, unmanned aerial vehicles, soft sets, neutrosophic sets, fractional calculus, big data analytics, and the mathematical foundations of convolutional neural network (CNNs). Soft Computing: Engineering Applications offers readers a comprehensive and in-depth understanding of various cutting-edge technologies that are transforming industries worldwide. The book explores soft computing techniques in a very systematic manner. It elucidates the concepts, theories, and applications of fuzzy sets, enabling readers to grasp the fundamentals and explore their applications in various fields. It provides new insight into unmanned aerial vehicle applications to fuzzy soft set based decision making. It then discusses new fixed point results in orthogonal neutrosophic generalized metric spaces and explores statistical convergence of triple sequences in a credibility space. The authors then provide readers with a solid grasp of the mathematical underpinnings of CNNs, enabling them to design, train, and optimize neural networks for image recognition, object detection, and other computer vision tasks. The authors also present new studies in fractional calculus and explores advanced visualization algorithms and techniques for big data analytics. Soft Computing will be useful for beginners and advanced researchers in engineering, applied sciences and healthcare professionals working in soft computing applications.




Mathematical Modeling and Soft Computing in Epidemiology


Book Description

This book describes the uses of different mathematical modeling and soft computing techniques used in epidemiology for experiential research in projects such as how infectious diseases progress to show the likely outcome of an epidemic, and to contribute to public health interventions. This book covers mathematical modeling and soft computing techniques used to study the spread of diseases, predict the future course of an outbreak, and evaluate epidemic control strategies. This book explores the applications covering numerical and analytical solutions, presents basic and advanced concepts for beginners and industry professionals, and incorporates the latest methodologies and challenges using mathematical modeling and soft computing techniques in epidemiology. Primary users of this book include researchers, academicians, postgraduate students, and specialists.




Advanced Mathematical Analysis and its Applications


Book Description

Advanced Mathematical Analysis and its Applications presents state-of-the-art developments in mathematical analysis through new and original contributions and surveys, with a particular emphasis on applications in engineering and mathematical sciences. New research directions are indicated in each of the chapters, and while this book is meant primarily for graduate students, there is content that will be equally useful and stimulating for faculty and researchers. The readers of this book will require minimum knowledge of real, complex, and functional analysis, and topology. Features Suitable as a reference for graduate students, researchers, and faculty Contains the most up-to-date developments at the time of writing.




Soft Computing in Materials Development and its Sustainability in the Manufacturing Sector


Book Description

This book focuses on the application of soft computing in materials and manufacturing sectors with the objective to offer an intelligent approach to improve the manufacturing process, material selection and characterization techniques for developing advanced new materials. It unveils different models and soft computing techniques applicable in the field of advanced materials and solves the problems to help the industry and scientists to develop sustainable materials for all purposes. The book focuses on the overall well-being of the environment for better sustenance and livelihood. Firstly, the authors discuss the implementation of soft computing in the various areas of engineering materials. They also review the latest intelligent technologies and algorithms related to the state-of-the-art methodologies of monitoring and effective implementation of sustainable engineering practices. Finally the authors examine the future generation of sustainable and intelligent monitoring techniques beneficial for manufacturing, and cover novel soft computing techniques for the purpose of effective manufacturing processes at par with the standards laid down by the International Standards of Organization (ISO). This book is intended for academics and researchers from all the fields of engineering interested in joining interdisciplinary initiatives on soft computing techniques for advanced materials and manufacturing.




Advances In Number Theory And Applied Analysis


Book Description

Presently, the exploration of the applications of different techniques and tools of number theory and mathematical analysis are extensively prevalent in various areas of engineering, mathematical, physical, biological and statistical sciences. This book will present the most recent developments in these two fields through contributions from eminent scientists and mathematicians worldwide.The book will present the current state of the art development in these two areas through original new contributions and surveys. As such, readers will find several useful tools and techniques to develop their skills and expertise in number theory and applied analysis. New research directions are also indicated in each of the chapters. This book is meant for graduate students, faculty and researchers willing to expand their knowledge in number theory and mathematical analysis. The readers of this book will require minimum prerequisites of analysis, topology, number theory and functional analysis.




Industry 5.0 for Smart Healthcare Technologies


Book Description

In this book, the role of Artificial Intelligence (AI), Internet of Things (IoT) and Blockchain in smart healthcare is explained through a detailed study of Artificial Neural Network, Fuzzy Set Theory, Intuitionistic Fuzzy Set, Machine Learning and Big Data technology. Industry 5.0 for Smart Healthcare Technologies: Utilizing Artificial Intelligence, Internet of Medical Things and Blockchain focuses on interesting applications of AI, promising advancements in IoT and important findings in Blockchain technology. When applied to smart healthcare technologies, Industry 5.0 offers numerous benefits that can revolutionize the healthcare industry. This book provides readers with insights and tools for enhanced patient care, remote patient monitoring, predictive analytics and early intervention of diseases, seamless data sharing and interoperability, telemedicine and virtual care, and a safer and more secure healthcare ecosystem. The authors examine novel computational algorithms for the processing of medical images, as well as novel algorithms for the processing of biosignals in detection of diseases. This book also explores systems for processing physiological parameters and discusses applications of AI techniques in the broader healthcare industry. The authors also investigate the importance of Augment Reality/Virtual Relatity (AR/VR) in the healthcare sector and examine the futuristic applications of Industry 5.0 in the healthcare sector. This book is intended for researchers and professionals working in interdisciplinary fields of computer engineering/science and healthcare. It will provide them with the tools to enhance diagnostics, optimize treatment plans, and empower patients to actively participate in their healthcare journey.




Fixed Point Theory and Fractional Calculus


Book Description

This book collects chapters on fixed-point theory and fractional calculus and their applications in science and engineering. It discusses state-of-the-art developments in these two areas through original new contributions from scientists across the world. It contains several useful tools and techniques to develop their skills and expertise in fixed-point theory and fractional calculus. New research directions are also indicated in chapters. This book is meant for graduate students and researchers willing to expand their knowledge in these areas. The minimum prerequisite for readers is the graduate-level knowledge of analysis, topology and functional analysis.




Edge-AI in Healthcare


Book Description

The book provides comprehensive research ideas about Edge-AI technology that can assist doctors in making better data-driven decisions. It provides insights for improving the healthcare industry by examining future trends, simplifying decision making and investigating structured and unstructured data. Edge-AI in Healthcare: Trends and Future Perspective is more than a comprehensive introduction to Artificial Intelligence as a tool in healthcare data. The book is split into five chapters covering the entire healthcare ecosystem. First section is introduction to Edge-AI in healthcare. It discusses data usage, modelling and simulation techniques as well as machine and deep learning approaches. The second section discusses the implementation of edge AI for smart healthcare. The topics discussed in this section include, AR/VR and cloud computing, big data management, algorithms, optimization, and IoMT techniques and methods. Third section covers role of Edge-AI in healthcare and the challenges and opportunities of the technologies. This section also provides case studies and discusses sustainability, security, privacy, and trust related to Edge-AI in healthcare. This book is intended to benefit researchers, academics, industry professionals, R & D organizations and students working in the field of healthcare, healthcare informatics and their applications.




Computational Statistical Methodologies and Modeling for Artificial Intelligence


Book Description

This book covers computational statistics-based approaches for Artificial Intelligence. The aim of this book is to provide comprehensive coverage of the fundamentals through the applications of the different kinds of mathematical modelling and statistical techniques and describing their applications in different Artificial Intelligence systems. The primary users of this book will include researchers, academicians, postgraduate students, and specialists in the areas of data science, mathematical modelling, and Artificial Intelligence. It will also serve as a valuable resource for many others in the fields of electrical, computer, and optical engineering. The key features of this book are: Presents development of several real-world problem applications and experimental research in the field of computational statistics and mathematical modelling for Artificial Intelligence Examines the evolution of fundamental research into industrialized research and the transformation of applied investigation into real-time applications Examines the applications involving analytical and statistical solutions, and provides foundational and advanced concepts for beginners and industry professionals Provides a dynamic perspective to the concept of computational statistics for analysis of data and applications in intelligent systems with an objective of ensuring sustainability issues for ease of different stakeholders in various fields Integrates recent methodologies and challenges by employing mathematical modeling and statistical techniques for Artificial Intelligence