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 A study-guide to probability and statistics that includes coverage of course concepts and 897 fully solved problems.

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 Fuzzy Cognitive Maps (FCM) constitute cognitive models in the form of fuzzy directed graphs consisting of two basic elements: the nodes, which basically correspond to “concepts” bearing different states of activation depending on the knowledge they represent, and the “edges” denoting the causal effects that each source node exercises on the receiving concept expressed through weights. Weights take values in the interval [-1,1], which denotes the positive, negative or neutral causal relationship between two concepts. An FCM can be typically obtained through linguistic terms, inherent to fuzzy systems, but with a structure similar to the neural networks, which facilitates data processing, and has capabilities for training and adaptation. During the last 10 years, an exponential growth of published papers in FCMs was followed showing great impact potential. Different FCM structures and learning schemes have been developed, while numerous studies report their use in many contexts with highly successful modeling results. The aim of this book is to fill the existing gap in the literature concerning fundamentals, models, extensions and learning algorithms for FCMs in knowledge engineering. It comprehensively covers the state-of-the-art FCM modeling and learning methods, with algorithms, codes and software tools, and provides a set of applications that demonstrate their various usages in applied sciences and engineering.

 For an introductory course in probability with high school algebra the only prerequisite.

 This book constitutes the refereed conference proceedings of the 16th IFIP WG 6.11 Conference on e-Business, e-Services and e-Society, I3E 2017, held in Delhi, India, in November 2017. The 45 revised full papers presented were carefully reviewed and selected from 92 submissions. They are organized in the following topical sections: Adoption of Smart Services; Assessment of ICT Enabled Smart Initiatives; Analytics for Smart Governance; Social Media and Web 3.0 for Smartness; and Smart Solutions for the Future.