This book covers novel research based on various computational intelligence topics, including deep learning, artificial intelligence, machine learning, neural networks, healthcare, solutions to various problems using fuzzy systems and their applications in cryptography, assignment problems, transportation problems, cloud computing, etc. The goal of writing this book is to promote advances in the field of computational intelligence systems and to aid in the dissemination of results concerning recent applications in the areas of computational intelligence system-based applications, its allied branches like artificial intelligence, deep learning, cloud computing, fuzzy system, etc... among working professionals, researchers, and educators. This book will be useful for Data Scientists, web developers, cryptographers, medical researchers, engineers, researchers, and graduate level students in computer science, data science, operations research, and mathematics. It provides novel applications as well as new theoretical developments required to understand current computational intelligence topics such as deep learning, machine learning, fuzzy based systems, and various other relevant fields. Graduate and postgraduate Computer Science, Engineering, Information Technology and Mathematics students, as well as teachers, can use it as a reference book because they can find applications that can be used to clarify specific concepts.

Applications of Computational Intelligence in Multi-Disciplinary Research provides the readers with a comprehensive handbook for applying the powerful principles, concepts, and algorithms of computational intelligence to a wide spectrum of research cases. The book covers the main approaches used in computational intelligence, including fuzzy logic, neural networks, evolutionary computation, learning theory, and probabilistic methods, all of which can be collectively viewed as soft computing. Other key approaches included are swarm intelligence and artificial immune systems. These approaches provide researchers with powerful tools for analysis and problem-solving when data is incomplete and when the problem under consideration is too complex for standard mathematics and the crisp logic approach of Boolean computing. Provides an overview of the key methods of computational intelligence, including fuzzy logic, neural networks, evolutionary computation, learning theory, and probabilistic methods Includes case studies and real-world examples of computational intelligence applied in a variety of research topics, including bioinformatics, biomedical engineering, big data analytics, information security, signal processing, machine learning, nanotechnology, and optimization techniques Presents a thorough technical explanation on how computational intelligence is applied that is suitable for a wide range of multidisciplinary and interdisciplinary research

"This book explores the complex world of computational intelligence, which utilizes computational methodologies such as fuzzy logic systems, neural networks, and evolutionary computation for the purpose of managing and using data effectively to address complicated real-world problems"--

The book is a timely report on advanced methods and applications of computational intelligence systems. It covers a long list of interconnected research areas, such as fuzzy systems, neural networks, evolutionary computation, evolving systems and machine learning. The individual chapters are based on peer-reviewed contributions presented at the 16th Annual UK Workshop on Computational Intelligence, held on September 7-9, 2016, in Lancaster, UK. The book puts a special emphasis on novels methods and reports on their use in a wide range of applications areas, thus providing both academics and professionals with a comprehensive and timely overview of new trends in computational intelligence.

The book is a timely report on advanced methods and applications of computational intelligence systems. It covers a long list of interconnected research areas, such as fuzzy systems, neural networks, evolutionary computation, evolving systems and machine learning. The individual chapters are based on peer-reviewed contributions presented at the 17th Annual UK Workshop on Computational Intelligence, held on September 6-8, 2017, in Cardiff, UK. The book puts a special emphasis on novels methods and reports on their use in a wide range of applications areas, thus providing both academics and professionals with a comprehensive and timely overview of new trends in computational intelligence.

This book at hand explores emerging scientific and technological areas in which Intelligent Computing Systems provide efficient solutions and, thus, may play a role in the years to come. It demonstrates how Intelligent Computing Systems make use of computational methodologies that mimic nature-inspired processes to address real world problems of high complexity for which exact mathematical solutions, based on physical and statistical modelling, are intractable. Common intelligent computational methodologies are presented including artificial neural networks, evolutionary computation, genetic algorithms, artificial immune systems, fuzzy logic, swarm intelligence, artificial life, virtual worlds and hybrid methodologies based on combinations of the previous. The book will be useful to researchers, practitioners and graduate students dealing with mathematically-intractable problems. It is intended for both the expert/researcher in the field of Intelligent Computing Systems, as well as for the general reader in the fields of Artificial and Computational Intelligence who wishes to learn more about the field of Intelligent Computing Systems and its applications. An extensive list of bibliographic references at the end of each chapter guides the reader to probe further into application area of interest to him/her.

This book presents the latest trends in and approaches to computational intelligence research and its application to intelligent systems. It covers a long list of interconnected research areas, such as fuzzy systems, neural networks, evolutionary computation, clustering and classification, machine learning, data mining, cognition and robotics, and deep learning. The individual chapters are based on peer-reviewed contributions presented at the 18th Annual UK Workshop on Computational Intelligence (UKCI-2018), held in Nottingham, UK on September 5-7, 2018. The book puts a special emphasis on novel methods and reports on their use in a wide range of applications areas, thus providing both academics and professionals with a comprehensive and timely overview of new trends in computational intelligence.