Jagdish Chand Bansal (editor) - Computationally Intelligent Systems and their Applications (Studies in Computational Intelligence, 950)

The series Studies in Computational Intelligence (SCI) publishes new developments and advances in the various areas of computational intelligencequickly and with a high quality. The intent is to cover the theory, applications, and design methods of computational intelligence, as embedded in the fields of engineering, computer science, physics and life sciences, as well as the methodologies behind them. The series contains monographs, lecture notes and edited volumes in computational intelligence spanning the areas of neural networks, connectionist systems, genetic algorithms, evolutionary computation, artificial intelligence, cellular automata, self-organizing systems, soft computing, fuzzy systems, and hybrid intelligent systems. Of particular value to both the contributors and the readership are the short publication timeframe and the world-wide distribution, which enable both wide and rapid dissemination of research output.

Indexed by SCOPUS, DBLP, WTI Frankfurt eG, zbMATH, SCImago.

All books published in the series are submitted for consideration in Web of Science.

More information about this series at http://www.springer.com/series/7092

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Computationally intelligent system is a new concept for advanced information processing. The objective of this system is to realize a new approach for analysing and creating flexible information processing of sensing, learning, recognizing and action taking. Computational intelligent is a part of artificial intelligence (AI) which includes the study of versatile components to empower or encourage savvy practices in intricate and evolving situations. This new trend of computational intelligence applications seek the adaptation of computational neural network algorithms and techniques in many application domains, including software systems, cybersecurity, human activity recognition and behavioural modelling. As such, the computational neural network algorithms can be refined to address problems in data-driven applications. The computationally intelligent system highly relies on numerical information supplied by manufacturers unlike AI. The book covers all the core technologies like neural networks, fuzzy systems and evolutionary computation and their applications in the systems.

This book aims to foster the computationally intelligent system, its features and applications. Original research and review articles with model and computationally intelligent system applications using computational algorithm are included as different chapters. The reader will learn on various computationally intelligent system applications and their behaviours in order to extract key features. The book will enable researchers from academia and industry to share innovative applications and creative solutions to common problems using computational intelligence.