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Krishnanand N. Kaipa, Debasish Ghose ... 248 pages - Publisher: Springer; (January, 2017) ... Language: English - ASIN: B01N7R22Z8 by Amazon.

This book provides a comprehensive account of the glowworm swarm optimization (GSO) algorithm, including details of the underlying ideas, theoretical foundations, algorithm development, various applications, and MATLAB programs for the basic GSO algorithm. It also discusses several research problems at different levels of sophistication that can be attempted by interested researchers. The generality of the GSO algorithm is evident in its application to diverse problems ranging from optimization to robotics. Examples include computation of multiple optima, annual crop planning, cooperative exploration, distributed search, multiple source localization, contaminant boundary mapping, wireless sensor networks, clustering, knapsack, numerical integration, solving fixed point equations, solving systems of nonlinear equations, and engineering design optimization. The book is a valuable resource for researchers as well as graduate and undergraduate students in the area of swarm intelligence and computational intelligence and working on these topics.

Soumya D. Mohanty ... 136 pages - Publisher: Chapman and Hall/CRC; (December, 2018) ... Language: English - ASIN: B07LCWSVMD by Amazon.

A core task in statistical analysis, especially in the era of Big Data, is the fitting of flexible, high-dimensional, and non-linear models to noisy data in order to capture meaningful patterns. This can often result in challenging non-linear and non-convex global optimization problems. The large data volume that must be handled in Big Data applications further increases the difficulty of these problems. Swarm Intelligence Methods for Statistical Regression describes methods from the field of computational swarm intelligence (SI), and how they can be used to overcome the optimization bottleneck encountered in statistical analysis.

Anand Nayyar, Dac-Nhuong Le, Nhu Gia Nguyen ... 314 pages - Publisher: Chapman and Hall/CRC; (October, 2018) ... Language: English - ASIN: B07HZS2JD8 by Amazon.

Ying Tan ... 323 pages - Publisher: Springer; (October, 2015) ... Language: English - ISBN-10: 3662463520 - ISBN-13: 978-3662463529

This book is devoted to the state-of-the-art in all aspects of fireworks algorithm (FWA), with particular emphasis on the efficient improved versions of FWA. It describes the most substantial theoretical analysis including basic principle and implementation of FWA and modeling and theoretical analysis of FWA. It covers exhaustively the key recent significant research into the improvements of FWA so far. In addition, the book describes a few advanced topics in the research of FWA, including multi-objective optimization (MOO), discrete FWA (DFWA) for combinatorial optimization, and GPU-based FWA for parallel implementation. In sequels, several successful applications of FWA on non-negative matrix factorization (NMF), text clustering, pattern recognition, and seismic inversion problem, and swarm robotics, are illustrated in details, which might shed new light on more real-world applications in future. Addressing a multidisciplinary topic, it will appeal to researchers and professionals in the areas of metahuristics, swarm intelligence, evolutionary computation, complex optimization solving, etc.

S. Chakraverty, Susmita Mall ... 157 pages - Publisher: CRC Press; (July, 2017) ... Language: English - ASIN: B0744Q3RW2 by Amazon.

Differential equations play a vital role in the fields of engineering and science. Problems in engineering and science can be modeled using ordinary or partial differential equations. Analytical solutions of differential equations may not be obtained easily, so numerical methods have been developed to handle them. Machine intelligence methods, such as Artificial Neural Networks (ANN), are being used to solve differential equations, and these methods are presented in Artificial Neural Networks for Engineers and Scientists: Solving Ordinary Differential Equations. This book shows how computation of differential equation becomes faster once the ANN model is properly developed and applied.

Max Tegmark ... 384 pages - Publisher: Knopf; (August, 2017) ... Language: English - ISBN-10: 1101946598 - ISBN-13: 978-1101946596 ... 

Nadia Nedjah, Leandro dos Santos Coelho, Luiza de Macedo Mourelle ... 211 pages - Publisher: Springer; (March, 2012) ... Language: English - ISBN-10: 3642261515 - ISBN-13: 978-3642261510 ...

The editors of this volume, Nadia Nedjah, Leandro dos Santos Coelho and Luiza de Macedo Mourelle, have done a superb job of assembling some of the most innovative and intriguing applications and additions to the methodology and theory of multi-objective swarm intelligence ― the immitation of social swarms behaviors for the solution of optimization problems with respect to many criteria.

Satchidananda Dehuri, A. K. Jagadev, M. Panda ... 201 pages - Publisher: Springer; (March, 2015) ...
Language: English - ISBN-10: 3662463083 - ISBN-13: 978-3662463086 ...

The aim of this book is to understand the state-of-the-art theoretical and practical advances of swarm intelligence. It comprises seven contemporary relevant chapters. In chapter 1, a review of Bacteria Foraging Optimization (BFO) techniques for both single and multiple criterions problem is presented. A survey on swarm intelligence for multiple and many objectives optimization is presented in chapter 2 along with a topical study on EEG signal analysis. Without compromising the extensive simulation study, a comparative study of variants of MOPSO is provided in chapter 3. Intractable problems like subset and job scheduling problems are discussed in chapters 4 and 7 by different hybrid swarm intelligence techniques. An attempt to study image enhancement by ant colony optimization is made in chapter 5. Finally, chapter 7 covers the aspect of uncertainty in data by hybrid PSO. 

Xin-She Yang ... 300 pages - Publisher: Springer; 1st edition (September, 2016) ... Language: English - ISBN-10: 331935681X - ISBN-13: 978-3319356815 ...

This timely review volume summarizes the state-of-the-art developments in nature-inspired algorithms and applications with the emphasis on swarm intelligence and bio-inspired computation. Topics include the analysis and overview of swarm intelligence and evolutionary computation, hybrid metaheuristic algorithms, bat algorithm, discrete cuckoo search, firefly algorithm, particle swarm optimization, and harmony search as well as convergent hybridization. Application case studies have focused on the dehydration of fruits and vegetables by the firefly algorithm and goal programming, feature selection by the binary flower pollination algorithm, job shop scheduling, single row facility layout optimization, training of feed-forward neural networks, damage and stiffness identification, synthesis of cross-ambiguity functions by the bat algorithm, web document clustering, truss analysis, water distribution networks, sustainable building designs and others. As a timely review, this book can serve as an ideal reference for graduates, lecturers, engineers and researchers in computer science, evolutionary computing, artificial intelligence, machine learning, computational intelligence, data mining, engineering optimization and designs.

J. Kennedy, R. C. Eberhart, Y. Shi ... 512 pages - Publisher: M. Kaufmann; (April, 2001) ...
Language: English - ISBN-10: 1558605959 - ISBN-13: 978-1558605954 ...

Traditional methods for creating intelligent computational systems have privileged private "internal" cognitive and computational processes. In contrast, Swarm Intelligence argues that human intelligence derives from the interactions of individuals in a social world and further, that this model of intelligence can be effectively applied to artificially intelligent systems. The authors first present the foundations of this new approach through an extensive review of the critical literature in social psychology, cognitive science, and evolutionary computation. They then show in detail how these theories and models apply to a new computational intelligence methodology―particle swarms―which focuses on adaptation as the key behavior of intelligent systems. Drilling down still further, the authors describe the practical benefits of applying particle swarm optimization to a range of engineering problems. Developed by the authors, this algorithm is an extension of cellular automata and provides a powerful optimization, learning, and problem solving method.

This important book presents valuable new insights by exploring the boundaries shared by cognitive science, social psychology, artificial life, artificial intelligence, and evolutionary computation and by applying these insights to the solving of difficult engineering problems. Researchers and graduate students in any of these disciplines will find the material intriguing, provocative, and revealing as will the curious and savvy computing professional. * Places particle swarms within the larger context of intelligent adaptive behavior and evolutionary computation. * Describes recent results of experiments with the particle swarm optimization (PSO) algorithm * Includes a basic overview of statistics to ensure readers can properly analyze the results of their own experiments using the algorithm. * Support software which can be downloaded from the publishers website, includes a Java PSO applet, C and Visual Basic source code.

Christian Blum, Daniel Merkle ... 286 pages - Publisher: Springer; (November, 2008) ...
Language: English - ISBN-10: 3540740880 - ISBN-13: 978-3540740889 ...

The laws that govern the collective behavior of social insects, flocks of birds, or fish schools continue to mesmerize researchers. While individuals are rather unsophisticated, in cooperation they can solve complex tasks, a prime example being the ability of ant colonies to find shortest paths between their nests and food sources. Task-solving results from self-organization, which often evolves from simple means of communication, either directly or indirectly via changing the environment, the latter referred to as stigmergy. Scientists have applied these principles in new approaches, for example to optimization and the control of robots. Characteristics of the resulting systems include robustness and flexibility. This field of research is now referred to as swarm intelligence. The contributing authors are among the top researchers in their domain. The book is intended to provide an overview of swarm intelligence to novices, and to offer researchers in the field an update on interesting recent developments. Introductory chapters deal with the biological foundations, optimization, swarm robotics, and applications in new-generation telecommunication networks, while the second part contains chapters on more specific topics of swarm intelligence research such as the evolution of robot behavior, the use of particle swarms for dynamic optimization, and organic computing.

Konstantinos E. Parsopoulos, Michael N. Vrahatis ... 328 pages - Publisher: IGI Global; 1st edition (January, 2010) ... Language: English - ISBN-10: 1615206663 - ISBN-13: 978-1615206667.

Ying Tan, Yuhui Shi, Li Li ... 657 pages - Publisher: Springer; 1st edition (September, 2016) ... Language: English - ASIN: B01IK5HJEQ by Amazon Digital Services ...

This two-volume set LNCS 9712 and LNCS 9713 constitutes the refereed proceedings of the 7th International Conference on Swarm Intelligence, ICSI 2016, held in Bali, Indonesia, in June 2016. The 130 revised regular papers presented were carefully reviewed and selected from 231 submissions. The papers are organized in 22 cohesive sections covering major topics of swarm intelligence and related areas such as trend and models of swarm intelligence research; novel swarm-based optimization algorithms; swarming behaviour; some swarm intelligence algorithms and their applications; hybrid search optimization; particle swarm optimization; PSO applications; ant colony optimization; brain storm optimization; fireworks algorithms; multi-objective optimization; large-scale global optimization; biometrics; scheduling and planning; machine learning methods; clustering algorithm; classification; image classification and encryption; data mining; sensor networks and social networks; neural networks; swarm intelligence in management decision making and operations research; robot control; swarm robotics; intelligent energy and communications systems; and intelligent and interactive and tutoring systems.

Marco Dorigo, Mauro Birattari, Xiaodong Li, M. López-Ibáñez, K. Ohkura, C. Pinciroli, T. Stützle ... 
304 pages - Publisher: Springer; 1st edition (August, 2016) ...
Language: English - ISBN-10: 3319444263 - ISBN-13: 978-3319444260 ...

This book constitutes the proceedings of the 10th International Conference on Swarm Intelligence, ANTS 2016, held in Brussels, Belgium, in September 2016.  The 18 full papers and 7 short papers presented in this volume were carefully reviewed and selected from 47 submissions. They are devoted to the field of swarm intelligence as a whole, without any bias towards specific research directions.

Maurice Clerc, Bijaya Ketan Panigrahi, Yuhui Shi, Meng-Hiot Lim ... 
544 pages - Publisher: Springer;  (January, 2011) ... Language: English - ISBN-10: 3642173896 - ISBN-13: 978-3642173899.

From nature, we observe swarming behavior in the form of ant colonies, bird flocking, animal herding, honey bees, swarming of bacteria, and many more.  It is only in recent years that researchers have taken notice of such natural swarming systems as culmination of some form of innate collective intelligence, albeit swarm intelligence (SI) - a metaphor that inspires a myriad of computational problem-solving techniques.  In computational intelligence, swarm-like algorithms have been successfully applied to solve many real-world problems in engineering and sciences. This handbook volume serves as a useful foundational as well as consolidatory state-of-art collection of articles in the field from various researchers around the globe.  It has a rich collection of contributions pertaining to the theoretical and empirical study of single and multi-objective variants of swarm intelligence based algorithms like particle swarm optimization (PSO), ant colony optimization (ACO), bacterial foraging optimization algorithm (BFOA), honey bee social foraging algorithms, and harmony search (HS).  With chapters describing various applications of SI techniques in real-world engineering problems, this handbook can be a valuable resource for researchers and practitioners, giving an in-depth flavor of what SI is capable of achieving.

Marco Dorigo, Mauro Birattari, Christian Blum, Maurice Clerc, Thomas Stützle, Alan Winfield ... 416 pages - Publisher: Springer; (October, 2008) ... Language: English - ISBN-10: 3540875263 - ISBN-13: 978-3540875260.

This book constitutes the refereed proceedings of the 6th International Workshop on Ant Colony Optimization and Swarm Intelligence, ANTS 2008, held in Brussels, Belgium, in September 2008. The 17 revised full papers, 24 revised short papers, and 10 extended abstracts presented were carefully reviewed and selected from 91 submissions. The papers cover theoretical and foundational aspects of computational intelligence and related disciplines with special focus on swarm intelligence and are devoted to behavioral models of social insects and new algorithmic approaches, empirical and theoretical research in swarm intelligence, applications such as ant colony optimization or particle swarm optimization, and theoretical and experimental research in swarm robotics systems.

The series of biannual international conferences “ANTS – International C- ference on Ant Colony Optimization and Swarm Intelligence”, now in its sixth edition, was started ten years ago, with the organization of ANTS’98. As some readers might recall, the first edition of ANTS was titled “ANTS’98 – From Ant Colonies to Artificial Ants: First International Workshop on Ant Colony Op- mization. ” In fact, at that time the focus was mainly on ant colony optimization (ACO), the first swarm intelligence algorithm to go beyond a pure scientific interest and to enter the realm of real-world applications. Interestingly, in the ten years after the first edition there has been a gr- ing interest not only for ACO, but for a number of other studies that belong more generally to the area of swarmintelligence. The rapid growth of the swarm intelligence field is attested by a number of indicators. First, the number of s- missions and participants to the ANTS conferences has steadily increased over the years. Second, a number of international conferences in computational - intelligence and related disciplines organize workshops on subjects such as swarm intelligence, ant algorithms, ant colony optimization, and particle swarm op- mization. Third, IEEE startedorganizing,in 2003, the IEEE SwarmIntelligence Symposium (in order to maintain unity in this growing field, we are currently establishing a cooperation agreement between IEEE SISandANTSsoastohave 1 IEEE SIS in odd years and ANTS in even years). Last, the Swarm Intelligence journal was born.