Applications of Computational Intelligence in Multi-Disciplinary Research

Applications of Computational Intelligence in Multi-Disciplinary Research provides readers with a comprehensive handbook for applying the powerful principles, concepts and algorithms of Computational Intelligence to a wide spectrum of research cases. Computational Intelligence is often used in conjunction with Artificial Intelligence, and though they are related, they use different approaches to arrive at applied solutions. Applications of Computational Intelligence in Multi-Disciplinary Research presents 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, which emulates human reasoning or biological systems. Other key approaches 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. The book contains numerous case studies and real-world applications of Computational Intelligence in areas such as bioinformatics, biomedical engineering, Big Data analytics, cloud security, cryptography, information security, digital signal and image processing, Machine Learning, microelectronics, nanotechnology, and optimization techniques. The book also explores interdisciplinary applications of Computational Intelligence. These use cases provide a fertile backdrop for scientists seeking to understand how they can apply Computational Intelligence to their own research Provides an overview of the key methods of Computational Intelligence, including fuzzy logic, neural networks, evolutionary computation, learning theory, and probabilistic methodsIncludes 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 techniquesProvides a thorough technical explanation of how Computational Intelligence is applied, suitable for a wide range of multidisciplinary and interdisciplinary research