The series "Studies in Big Data" (SBD) publishes new developments and advances in the various areas of Big Data-quickly and with a high quality. The intent is to cover the theory, research, development, and applications of Big Data, as embedded in the fields of engineering, computer science, physics, economics and life sciences. The books of the series refer to the analysis and understanding of large, complex, and/or distributed data sets generated from recent digital sources coming from sensors or other physical instruments as well as simulations, crowd sourcing, social networks or other internet transactions, such as emails or video click streams and other. The series contains monographs, lecture notes and edited volumes in Big Data spanning the areas of computational intelligence incl. neural networks, evolutionary computation, soft computing, fuzzy systems, as well as artificial intelligence, data mining, modern statistics and Operations research, as well as self-organizing 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.More information about this series at

The current economics of the fish protein industry demand rapid, accurate and expressive prediction algorithms at every step of protein production especially with the challenge of global climate change. This help to predict and analyze functional and nutritional quality then consequently control food allergies in hyper allergic patients. As, it is quite expensive and time-consuming to know these concentrations by the lab experimental tests, especially to conduct large-scale projects. Therefore, this paper introduced a new intelligent algorithm using adaptive neuro-fuzzy inference system based on whale optimization algorithm. This algorithm is used to predict the concentration levels of bioactive amino acids in fish protein hydrolysates at different times during the year. The whale optimization algorithm is used to determine the optimal parameters in adaptive neuro-fuzzy inference system. The results of proposed algorithm are compared with others and it is indicated the higher performance of the proposed algorithm.

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The Computer Communications and Networks series is a range of textbooks, monographs and handbooks. It sets out to provide students, researchers and nonspecialists alike with a sure grounding in current knowledge, together with comprehensible access to the latest developments in computer communications and networking.Emphasis is placed on clear and explanatory styles that support a tutorial approach, so that even the most complex of topics is presented in a lucid and intelligible manner. Apart from any fair dealing for the purposes of research or private study, or criticism or review, as permitted under the Copyright, Designs and Patents Act 1988, this publication may only be reproduced, stored or transmitted, in any form or by any means, with the prior permission in writing of the publishers, or in the case of reprographic reproduction in accordance with the terms of licenses issued by the Copyright Licensing Agency. Enquiries concerning reproduction outside those terms should be sent to the publishers. The use of registered names, trademarks, etc., in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant laws and regulations and therefore free for general use. The publisher makes no representation, express or implied, with regard to the accuracy of the information contained in this book and cannot accept any legal responsibility or liability for any errors or omissions that may be made. Ajith Abraham Cover design: SPi Publisher ServicesPrinted on acid-free paper Springer is part of Springer Science+Business Media (www.springer.com) PrefaceSocial networks provide a powerful abstraction of the structure and dynamics of diverse kinds of people or people-to-technology interaction. Web 2.0 has enabled a new generation of Web-based communities, social networks, and folksonomies to facilitate collaboration among different communities. Social network analysis is a rapidly growing field within the Web intelligence domain. The recent developments in Web 2.0 have provided more opportunities to investigate the dynamics and structure of Web-based social networks. Recent trends also indicate the usage of social networks as a key feature for next-generation usage and exploitation of the Web. This book provides an opportunity to compare and contrast the ethological approach to social behavior in animals (including the study of animal tracks and learning by members of the same species) with web-based evidence of social interaction, perceptual learning, information granulation, the behavior of humans, and affinities between web-based social networks. The main topics cover the design and use of various computational intelligence tools and software, simulations of social networks, representation and analysis of social networks, use of semantic networks in the design, and community-based research issues such as knowledge discovery, privacy and protection, and visualization. This book presents some of the latest advances of various topics in intelligence social net...

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