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The book focuses on machine learning. Divided into three parts, the first part discusses the feature selection problem. The second part then describes the application of machine learning in the classification problem, while the third part presents an overview of real-world applications of swarm-based optimization algorithms. The concept of machine learning (ML) is not new in the field of computing. However, due to the ever-changing nature of requirements in today’s world it has emerged in the form of completely new avatars. Now everyone is talking about ML-based solution strategies for a given problem set. The book includes research articles and expository papers on the theory and algorithms of machine learning and bio-inspiring optimization, as well as papers on numerical experiments and real-world applications.
This book presents a compilation of the most recent implementation of artificial intelligence methods for solving different problems generated by the COVID-19. The problems addressed came from different fields and not only from medicine. The information contained in the book explores different areas of machine and deep learning, advanced image processing, computational intelligence, IoT, robotics and automation, optimization, mathematical modeling, neural networks, information technology, big data, data processing, data mining, and likewise. Moreover, the chapters include the theory and methodologies used to provide an overview of applying these tools to the useful contribution to help to face the emerging disaster. The book is primarily intended for researchers, decision makers, practitioners, and readers interested in these subject matters. The book is useful also as rich case studies and project proposals for postgraduate courses in those specializations.
Advancements in manufacturing strategies and systems have sparked a profound transformation, ushering in a new era of efficiency, precision, and sustainability, driven by the integration of automation, artificial intelligence, and advanced materials, reshaping industries, boosting productivity, reducing costs, and improving the overall quality of products. This book focuses on practical applications of manufacturing technologies, providing case studies and real-world examples of how these advancements in manufacturing are being implemented to solve manufacturing challenges and improve efficiency. Manufacturing Strategies and Systems: Technologies, Processes, and Machine Tools presents numeri...
There is no industry left where artificial intelligence is not used in some capacity. The application of this technology has already stretched across a multitude of domains including law and policy; it will soon permeate areas beyond anyone’s imagination. Technology giants such as Google, Apple, and Facebook are already investing their money, effort, and time toward integrating artificial intelligence. As this technology continues to develop and expand, it is critical for everyone to understand the various applications of artificial intelligence and its full potential. The Handbook of Research on Innovative Management Using AI in Industry 5.0 uncovers new and innovative features of artificial intelligence and how it can help in raising economic efficiency at both micro and macro levels and provides a deeper understanding of the relevant aspects of artificial intelligence impacting efficacy for better output. Covering topics such as consumer behavior, information technology, and personalized banking, it is an ideal resource for researchers, academicians, policymakers, business professionals, companies, and students.
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 th...
The global supply chain expanded significantly in the last decades of the 20th century, especially in the automobile, food, and textile industries. This growth of the globalized business era brings both challenges and motivation for researchers and practitioners with interests in logistics and supply chain management. Logistics and Supply Chain Management in the Globalized Business Era provides an introduction as well as up-to-date information in the logistics and supply chain management fields. The book focuses on applying theory to practices and provides both quantitative and qualitative methods for decision makers; additionally, it details current information regarding digitalization, information technology, and optimization techniques. It is ideal for supply chain managers, executives, operations managers, business owners, suppliers, researchers, postgraduate students, laypersons, researchers, and professionals.
Faced with chaotic environments, it is not possible to make totally efficient forecasts, especially when it is necessary to analyze events with multiple variables and micro, small, and medium enterprises (MSMEs) constantly face events that escape the laws of the market. The handling that has been given to the crisis caused by the coronavirus has been trial and error, and the economic, social, and environmental results remain to be seen. The markets and the world are chaotic. With the markets in chaos due to the COVID-19 pandemic, it is important to look at the methods used in these environments to promote business success. The Handbook of Research on Management Techniques and Sustainability ...