Computational Intelligence In The Industry 40

This book discusses the importance of using industrial intelligence in collaboration with computational intelligence in forming a smart system for diverse applications. It further illustrates the challenges and deployment issues in industrial resolution. The text highlights innovation and applications of computational agents and the industrial intelligence era to automate the requirements as per Industry 4.0. This book: Discusses computational agents for handling automation issues and the role of ethics in industrial resolution Presents intelligence approaches for products, operations, systems, and services Illustrates the fundamentals of computational intelligence to forecast and analyze the requirements of society for automation as well as recent innovations and applications Highlights computation intelligence approaches in reducing human effort and automating the analysis of the production unit Showcases current innovation and applications of computational agents and industrial intelligence as per Industry 4.0 The text is primarily written for senior undergraduate and graduate students, and academic researchers in diverse fields including electrical engineering, electronics, and communication engineering, industrial engineering, manufacturing engineering and computer science, and engineering.

Computational Intelligence Assisted Design framework mobilises computational resources, makes use of multiple Computational Intelligence (CI) algorithms and reduces computational costs. This book provides examples of real-world applications of technology. Case studies have been used to show the integration of services, cloud, big data technology and space missions. It focuses on computational modelling of biological and natural intelligent systems, encompassing swarm intelligence, fuzzy systems, artificial neutral networks, artificial immune systems and evolutionary computation. This book provides readers with wide-scale information on CI paradigms and algorithms, inviting readers to implement and problem solve real-world, complex problems within the CI development framework. This implementation framework will enable readers to tackle new problems without difficulty through a few tested MATLAB source codes

This book discusses the importance of using industrial intelligence in collaboration with computational intelligence in forming a smart system for diverse applications. It further illustrates the challenges and deployment issues in industrial resolution. The text highlights innovation and applications of computational agents and the industrial intelligence era to automate the requirements as per industry 4.0. This book: - Discusses computational agents for handling automation issues and the role of ethics in industrial resolution. - Presents intelligence approaches for products, operations, systems, and services. - Illustrates the fundamentals of computational intelligence to forecast and analyze the requirements of society for automation as well as recent innovations and applications. - Highlights computation intelligence approaches in reducing human effort and automating the analysis of the production unit. - Showcases current innovation and applications of computational agents and Industrial Intelligence as per industry 4.0. The text is primarily written for senior undergraduate, graduate students, and academic researchers in diverse fields including electrical engineering, electronics, and communications engineering, industrial engineering, manufacturing engineering, computer science, and engineering.

This book is intended to help management and other interested parties such as engineers, to understand the state of the art when it comes to the intersection between AI and Industry 4.0 and get them to realise the huge possibilities which can be unleashed by the intersection of these two fields. We have heard a lot about Industry 4.0, but most of the time, it focuses mainly on automation. In this book, the authors are going a step further by exploring advanced applications of Artificial Intelligence (AI) techniques, ranging from the use of deep learning algorithms in order to make predictions, up to an implementation of a full-blown Digital Triplet system. The scope of the book is to showcase what is currently brewing in the labs with the hope of migrating these technologies towards the factory floors. Chairpersons and CEOs must read these papers if they want to stay at the forefront of the game, ahead of their competition, while also saving huge sums of money in the process.

The field of computational intelligence has grown tremendously over that past five years, thanks to evolving soft computing and artificial intelligent methodologies, tools and techniques for envisaging the essence of intelligence embedded in real life observations. Consequently, scientists have been able to explain and understand real life processes and practices which previously often remain unexplored by virtue of their underlying imprecision, uncertainties and redundancies, and the unavailability of appropriate methods for describing the incompleteness and vagueness of information represented. With the advent of the field of computational intelligence, researchers are now able to explore and unearth the intelligence, otherwise insurmountable, embedded in the systems under consideration. Computational Intelligence is now not limited to only specific computational fields, it has made inroads in signal processing, smart manufacturing, predictive control, robot navigation, smart cities, and sensor design to name a few. Recent Trends in Computational Intelligence Enabled Research: Theoretical Foundations and Applications explores the use of this computational paradigm across a wide range of applied domains which handle meaningful information. Chapters investigate a broad spectrum of the applications of computational intelligence across different platforms and disciplines, expanding our knowledge base of various research initiatives in this direction. This volume aims to bring together researchers, engineers, developers and practitioners from academia and industry working in all major areas and interdisciplinary areas of computational intelligence, communication systems, computer networks, and soft computing. Provides insights into the theory, algorithms, implementation, and application of computational intelligence techniques Covers a wide range of applications of deep learning across various domains which are researching the applications of computational intelligence Investigates novel techniques and reviews the state-of-the-art in the areas of machine learning, computer vision, soft computing techniques

The book examines leading Industry 4.0 and 5.0 and Industrial Internet of Things technologies enhanced with computational intelligence (CI) techniques. The book covers modelling, controls, estimations, applications, and systems. It considers this multi-disciplinary domain that is based on data collected from smart sensors.

This book is addressed to young researchers and engineers in the fields of Computational Science and Artificial Intelligence, ranging from innovative computational methods to digital machine learning tools and their coupling used for solving challenging industrial and societal problems.This book provides the latest knowledge from jointly academic and industries experts in Computational Science and Artificial Intelligence fields for exploring possibilities and identifying challenges of applying Computational Sciences and AI methods and tools in industrial and societal sectors.

This book comprehensively addresses computational intelligence, including the theories, methodologies and techniques underlying this evolving field, as well as its potential uses in various domains across the entire spectrum of the sciences (the natural sciences, health sciences, engineering, social sciences, and humanities) and in various types of business. Computational intelligence is rapidly spreading into all kinds of products and services. This calls for the adaptation of existing theories, methodologies and techniques – and the development of wholly new ones – to ensure the successful implementation of new intelligent products and services in various domains related to public organizations, businesses and everyday life. This book gathers contributions from various experts working on different aspects and implementations of computational intelligence, which address new developments in theory, analytical and numerical simulation and modeling, experimentation, deployment and case studies, results of laboratory or field operational tests, and ongoing advances in computational intelligence. It is intended for a broad audience, including researchers, engineers, policymakers, industry experts, and students, offering these readers essential information on and new inspirations regarding the potential of computational intelligence.

This book covers the applications of computational intelligence techniques in business systems and advocates how these techniques are useful in modern business operations. The book redefines the computational intelligence foundations, the three pillars - neural networks, evolutionary computation, and fuzzy systems. It also discusses emerging areas such as swarm intelligence, artificial immune systems (AIS), support vector machines, rough sets, and chaotic systems. The other areas have also been demystified in the book to strengthen the range of computational intelligence techniques such as expert systems, knowledge-based systems, and genetic algorithms. Therefore, this book will redefine the role of computational intelligence techniques in modern business system operations such as marketing, finance & accounts, operations, personnel management, supply chain management, and logistics. Besides, this book guides the readers through using them to model, discover, and interpret new patterns that cannot be found through statistical methods alone in various business system operations. This book reveals how computational intelligence can inform the design and integration of services, architecture, brand identity, and product portfolio across the entire enterprise. The book will provide insights into research gaps, open challenges, and unsolved computational intelligence problems. The book will act as a premier reference and instant material for all the users who are contributing/practicing the adaptation of computational intelligence modern techniques in business systems.

In theory, there is no difference between theory and practice. But, in practice, there is. Jan L. A. van de Snepscheut The ?ow of academic ideas in the area of computational intelligence has penetrated industry with tremendous speed and persistence. Thousands of applications have proved the practical potential of fuzzy logic, neural networks, evolutionary com- tation, swarm intelligence, and intelligent agents even before their theoretical foundation is completely understood. And the popularity is rising. Some software vendors have pronounced the new machine learning gold rush to “Transfer Data into Gold”. New buzzwords like “data mining”, “genetic algorithms”, and “swarm optimization” have enriched the top executives’ vocabulary to make them look more “visionary” for the 21st century. The phrase “fuzzy math” became political jargon after being used by US President George W. Bush in one of the election debates in the campaign in 2000. Even process operators are discussing the perf- mance of neural networks with the same passion as the performance of the Dallas Cowboys. However, for most of the engineers and scientists introducing computational intelligence technologies into practice, looking at the growing number of new approaches, and understanding their theoretical principles and potential for value creation becomes a more and more dif?cult task.