image: With the Internet, the proliferation of Big Data, and autonomous systems, mankind has entered into an era of 'digital obesity'. In this century, computational intelligence, such as thinking machines, have been brought forth to process complex human problems in a wide scope of areas -- from social sciences, economics and biology, medicine and social networks, to cyber security. The Handbook on Computational Intelligence (in 2 Volumes) prompts readers to look at these problems from a non-traditional angle. It takes a step by step approach, supported by case studies, to explore the issues that have arisen in the process. The Handbook covers many classic paradigms, as well as recent achievements and future promising developments to solve some of these very complex problems. Volume one explores the subjects of fuzzy logic and systems, artificial neural networks, and learning systems. Volume two delves into evolutionary computation, hybrid systems, as well as the applications of computational intelligence in decision making, the process industry, robotics, and autonomous systems. This work is a 'one-stop-shop' for beginners, as well as an inspirational source for more advanced researchers. It is a useful resource for lecturers and learners alike. view more
Credit: World Scientific, 2016
We are witnessing an increased interest in intelligent systems; the quest for making machines to help, replace and act as humans has been for some time around.
However, only now the state of development of the technology made it possible to be approached so close that we are already surrounded by some products and will be further more in the near future which really have elements of "intelligence"; how to do this, what we can achieve and where the next steps will be? The answers to these questions one can find in this unique set of two volumes, 5 parts and 25+ chapters blended into a single Handbook -- something any student, graduate, researcher and expert must have.
Computational Intelligence is a set of computational techniques, methodologies, algorithms, systems that borrow from nature (human brain, individual self-development and evolution, populational evolution, reasoning by humans, etc.) and solve complex problems that are other wise not completely or fully addressed by the traditional first principles type of approaches, statistics, etc. The main branches of it include fuzzy sets and systems, artificial neural networks and evolutionary computation.
"This is a one stop shop written by experts in a very accessible way yet presenting the latest cutting edge results," said Professor Plamen Angelov, who is the editor of the Handbook.
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More information about "Handbook on Computational Intelligence (in 2 Volumes)." The book retails at US$295 / £195 (hardcover). If you require a review copy, any additional information, or would like to interview the author(s), please contact Jason Lim at cjlim@wspc.com.sg.
About the editor:
The editor (Plamen Angelov) is a full Professor at Lancaster University, UK, holds MEng (1993), PhD (1989) and DSc (2015) degrees. He is also a Fellow of the IEEEE and IET as well as a member of the Board of Governors of the Systems, Man and Cybernetics (SMC) Society of the IEEE as well as of the Intenrational Neural Networks Society (INNS). He has 30 years of professional experience in high level research and leads the Data Science group at the School of Computing and Communications which includes over 20 academics, researchers and PhD students and is one of the eight groups of the School. Prof. Angelov is a founding Chair of the Technical Committee (TC) on Evolving Intelligent Systems within the SMC Society and a past chair of the Standards Committee of the COmputational Intelligence Society of the IEEE; he is also a member of several other TCs (TC on Neural Networks, TC on Fuzzy Systems; TC on Diagnostics and Prognostics). Prof. Angelov has authored or co-authored over 200 peer-reviewed publications in leading journals, peer-reviewed conference proceedings, 5 patents, two research monographs (by Wiley, 2012 and Springer, 2002) and over a dozen other books. These publications has been cited over 4600 times (Google Scholar, March 2016) with an h-index of 34; i10-index is 71. He and his co-authors and students received a number of IEEE best paper awards (2006, 2009, 2012, 2013) as well as one of his papers was nominated for outstanding IEEE Transactions paper (2010). His most cited paper has over 700 citations. He has an active research portfolio in the area of computational intelligence and machine learning and internationally recognised results into online and evolving learning and algorithms for knowledge extraction in the form of human-intelligible fuzzy rule-based systems. Prof. Angelov leads numerous projects (including several multimillion ones) funded by UK research councils, EU, industry, UK Ministry of Defence. His research was recognised by 'The Engineer Innovation and Technology 2008 Special Award' and 'For outstanding Services' (2013) by IEEE and INNS. He is also the founding co-Editor-in-Chief of Springer's journal on Evolving Systems and Associate Editor of the leading international scientific journals in this area, including IEEE Transactions on Cybernetics, IEEE Transactions on Fuzzy Systems and several other journals including Applied Soft Computing, Fuzzy Sets and Systems, Soft Computing, etc. He was General Chair of primes conferences (IJCNN-2013, Dallas, Texas, 4-9 August 2013, Texas, USA; INNS inaugural Conference on Big Data, San Francisco, August, 2015; INNS Big Data2016, Greece; UKCI2016; IRAS2016) and Programme Committee co-Chair of prime conferences (IJCNN2016, Vancouver; FUZZ-IEEE-2014, July 2014, Beijing, China; IEEE Intelligent Systems'14, Warszaw, Poland; IS16, Sofia); founding General co- Chair of a series of annual IEEE conferences on Evolving and Adaptive Intelligent Systems. Prof. Angelov is often acting as a Visiting Professor (in Brazil, 2007 and 2014; Germany, 2006; Spain, 2010 and 2015; France, 2014; Bulgaria, 2011-14) regularly gives invited and plenary talks at leading companies and universities. Prof. Angelov is a member of the Special Interest Group (SIG) on Autonomous Machine Learning, International Neural Network Society, since 2008, co-ordinator of the Working Group on Data Mining and Learning to EUSFLAT since 2007, member of ISGEC (International Society of Genetic and Evolutionary Computation) and its Council of Authors, since 2002; member of the Senior Members sub-committee, IEEE, 2008-2010; North American Fuzzy Information Processing Society, NAFIPS, 2001,2005; member of the Innovation Award Committee for the World Congress on Nature and Biologically Inspired Computing, December 2009. Prof. Angelov gave over a dozen plenary and key note talks at high profile conferences. More information can be found at his web site http://www.lancs.ac.uk/staff/angelov
About World Scientific
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For more information, contact Jason Lim at cjlim@wspc.com.sg.