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"Like its three predecessors, this fourth volume in its series covers cutting-edge natural computing and agent-based methodologies in computational finance and economics, option model calibration, financial trend reversal detection, algorithmic trading and more."

"This book is very easy to read and one can gain a quick snapshot of computational issues arising in financial mathematics. SIAM review (46, 2004). The fourth edition is thoroughly revised and extended. Major revisions concern topics like calibration, Monte Carlo Methods, American options, exotic options and Algorithms for Bermuda Options. New figures, more exercises, more background material make this guide to the world of financial engineering a real must-to-have for everyone working in FE. "

"The latest volume in the Springer Handbooks of Computational Statistics series covers the full range of finance, including the modern class of financial tools, computational efficient algorithms, the pricing of complex products, risk behavior and much more. "

"This book highlights recent research advances in unsupervised learning using natural computing techniques such as artificial neural networks, evolutionary algorithms, swarm intelligence, artificial immune systems, artificial life, quantum computing, DNA computing, and others. The book also includes information on the use of natural computing techniques for unsupervised learning tasks. It features several trending topics, such as big data scalability, wireless network analysis, engineering optimization, social media, and complex network analytics. It shows how these applications have triggered a number of new natural computing techniques to improve the performance of unsupervised learning methods. With this book, the readers can easily capture new advances in this area with systematic understanding of the scope in depth. Readers can rapidly explore new methods and new applications at the junction between natural computing and unsupervised learning. Includes advances on unsupervised learning using natural computing techniquesReports on topics in emerging areas such as evolutionary multi-objective unsupervised learningFeatures natural computing techniques such as evolutionary multi-objective algorithms and many-objective swarm intelligence algorithms"

"This book features research related to computational intelligence and energy and thermal aware management of computing resources. The authors publish original and timely research in current areas of power, energy, temperature, and environmental engineering as and advances in computational intelligence that are benefiting the fields. Topics include signal processing architectures, algorithms, and applications; biomedical informatics and computation; artificial intelligence and machine learning; green technologies in information; and more. The book includes contributions from a wide range of researchers, academicians, and industry professionals. The book is made up both of extended papers presented at the International Conference on Intelligent Computing and Sustainable System (ICICSS 2018), September 20-21, 2018, and other accepted papers on R&D and original research work related to the practice and theory of technologies to enable and support Intelligent Computing applications."