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Emerging Research On Swarm Intelligence And Algorithm Optimization
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Book Synopsis Emerging Research on Swarm Intelligence and Algorithm Optimization by : Shi, Yuhui
Download or read book Emerging Research on Swarm Intelligence and Algorithm Optimization written by Shi, Yuhui and published by IGI Global. This book was released on 2014-07-31 with total page 369 pages. Available in PDF, EPUB and Kindle. Book excerpt: Throughout time, scientists have looked to nature in order to understand and model solutions for complex real-world problems. In particular, the study of self-organizing entities, such as social insect populations, presents a new opportunity within the field of artificial intelligence. Emerging Research on Swarm Intelligence and Algorithm Optimization discusses current research analyzing how the collective behavior of decentralized systems in the natural world can be applied to intelligent system design. Discussing the application of swarm principles, optimization techniques, and key algorithms being used in the field, this publication serves as an essential reference for academicians, upper-level students, IT developers, and IT theorists.
Book Synopsis Swarm Intelligence Optimization by : Abhishek Kumar
Download or read book Swarm Intelligence Optimization written by Abhishek Kumar and published by John Wiley & Sons. This book was released on 2021-01-07 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: Resource optimization has always been a thrust area of research, and as the Internet of Things (IoT) is the most talked about topic of the current era of technology, it has become the need of the hour. Therefore, the idea behind this book was to simplify the journey of those who aspire to understand resource optimization in the IoT. To this end, included in this book are various real-time/offline applications and algorithms/case studies in the fields of engineering, computer science, information security, and cloud computing, along with the modern tools and various technologies used in systems, leaving the reader with a high level of understanding of various techniques and algorithms used in resource optimization.
Book Synopsis Swarm Intelligence Algorithms (Two Volume Set) by : Adam Slowik
Download or read book Swarm Intelligence Algorithms (Two Volume Set) written by Adam Slowik and published by CRC Press. This book was released on 2021-01-26 with total page 379 pages. Available in PDF, EPUB and Kindle. Book excerpt: Swarm intelligence algorithms are a form of nature-based optimization algorithms. Their main inspiration is the cooperative behavior of animals within specific communities. This can be described as simple behaviors of individuals along with the mechanisms for sharing knowledge between them, resulting in the complex behavior of the entire community. Examples of such behavior can be found in ant colonies, bee swarms, schools of fish or bird flocks. Swarm intelligence algorithms are used to solve difficult optimization problems for which there are no exact solving methods or the use of such methods is impossible, e.g. due to unacceptable computational time. This set comprises two volumes: Swarm Intelligence Algorithms: A Tutorial and Swarm Intelligence Algorithms: Modifications and Applications. The first volume thoroughly presents the basics of 24 algorithms selected from the entire family of swarm intelligence algorithms. It contains a detailed explanation of how each algorithm works, along with relevant program codes in Matlab and the C ++ programming language, as well as numerical examples illustrating step-by-step how individual algorithms work. The second volume describes selected modifications of these algorithms and presents their practical applications. This book presents 24 swarm algorithms together with their modifications and practical applications. Each chapter is devoted to one algorithm. It contains a short description along with a pseudo-code showing the various stages of its operation. In addition, each chapter contains a description of selected modifications of the algorithm and shows how it can be used to solve a selected practical problem.
Book Synopsis Swarm Intelligence by : Christian Blum
Download or read book Swarm Intelligence written by Christian Blum and published by Springer Science & Business Media. This book was released on 2008-09-24 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book’s contributing authors are among the top researchers in swarm intelligence. The book is intended to provide an overview of the subject to novices, and to offer researchers 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.
Download or read book Swarm Intelligence written by Fouad Sabry and published by One Billion Knowledgeable. This book was released on 2021-01-18 with total page 113 pages. Available in PDF, EPUB and Kindle. Book excerpt: What Is Swarm Intelligence - Traders deciding on the next big market bet. - A navigation app quickly mapping out a less-explored area. - Fashion brands choosing the hottest color of the season. - An airport managing fight delays. What do these scenarios have in common? In each one, swarm intelligence blends global and local insight to improve how businesses make decisions. Swarm intelligence is a form of artificial intelligence (AI) inspired by the insect kingdom. In nature, it describes how honeybees migrate, how ants form perfect trails, and how birds flock. In the world of AI, swarm systems draw input from individual people or machine sensors and then use algorithms to optimize the overall performance of the group or system in real time. Consider Waze, the popular road navigation app that uses swarm intelligence to create and modify maps. Starting with limited digital maps, it began making tweaks based on its users’ GPS data along with manual map modifications by registered users. Entire cities have been mapped using this method, as was the case in Costa Rica’s capital, San José. And just as ants signal danger to their counterparts, so too do Waze users contribute live information from accident locations and traffic jams. Swarm intelligence is now being used to predict everything from the outcome of the Super Bowl to fashion trends to major political events. Using swarm intelligence, investors can better predict market movements, and retailers can more accurately forecast sales. How You Will Benefit By the end of reading this book, you will have the answers to the public top 100 questions, queries, issues, doubts, problems and inquiries. Most importantly, you will be able master the discussion about the following topics in Swarm Intelligence, and explore the new ways of thinking about life and business: 01 - Fundamental Concepts: Definition, Systems, Nature 02 - Models of Swarm Behavior: Boids, Self-Propelled Particles 03 - Optimization Problem: Elements, Formulations, and Search Solutions 04 - Meta-Heuristic Nature Inspired Optimization Algorithms Inspired by Swarm Intelligence 05 - Meta-Heuristic and Monkeys Problems: Infinite, Finite, and the difference 06 - Common Algorithmic Characteristics and Comparisons: Ant Colony Optimization, Bee Colony Optimization, Bat Algorithm, Cuckoo Search, Particle Swarm Optimization, Firefly Algorithm, Flower Pollination Algorithm, Swarm Intelligence Application Areas, Travelling Salesman Problem, Telecommunication, Image Processing, Engineering Design, Vehicle Routing 07 - Swarm Intelligence Systems: Taxonomy, Natural vs. Artificial, Scientific vs. Engineering 08 - Examples of Swarm Intelligence Systems: Foraging Behavior of Ants, Clustering by a Swarm of Robots, Exploitation of Collective Behaviors of Animal Societies, Swarm-based Data Analysis 09 - Properties of Swarm Intelligence Systems: Individual, Homogeneous, Interaction, Self-Organized 10 - Studies and Applications of Swarm Intelligence Systems: Clustering Behavior of Ants, Nest Building Behavior of Wasp and Termites, Flocking and Schooling in Birds and Fish, Any Colony Optimization, Particle Swarm Optimization, Swarm-based Network Management, Cooperative Behavior in Swarm of Robots. 11- Swarm Intelligence as a Whole New Way of Thinking About Business: Perspective and Advantages 12 - Swarm Intelligence Foraging for Solutions in Telecommunication, Information Technology, Logistics, Manufacturing. 13 - Advantages of Swarm Intelligence for Organizations: Simple Rules Rule, Raiding New Markets, A swarm of Possibilities.
Book Synopsis Swarm Intelligence by : Abhishek Sharma
Download or read book Swarm Intelligence written by Abhishek Sharma and published by CRC Press. This book was released on 2022-02-01 with total page 141 pages. Available in PDF, EPUB and Kindle. Book excerpt: Swarm intelligence is one of the fastest growing subfields of artificial intelligence and soft computing. This field includes multiple optimization algorithms to solve NP-hard problems for which conventional methods are not effective. It inspires researchers in engineering sciences to learn theories from nature and incorporate them. Swarm Intelligence: Foundation, Principles, and Engineering Applications provides a comprehensive review of new swarm intelligence techniques and offers practical implementation of Particle Swarm Optimization (PSO) with MATLAB code. The book discusses the statistical analysis of swarm optimization techniques so that researchers can analyse their experiment design. It also includes algorithms in social sectors, oil and gas industries, and recent research findings of new optimization algorithms in the field of engineering describing the implementation in machine learning. This book is written for students of engineering, research scientists, and academicians involved in the engineering sciences.
Book Synopsis Recent Algorithms and Applications in Swarm Intelligence Research by : Shi, Yuhui
Download or read book Recent Algorithms and Applications in Swarm Intelligence Research written by Shi, Yuhui and published by IGI Global. This book was released on 2012-11-30 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advancements in the nature-inspired swarm intelligence algorithms continue to be useful in solving complicated problems in nonlinear, non-differentiable, and un-continuous functions as well as being applied to solve real-world applications. Recent Algorithms and Applications in Swarm Intelligence Research highlights the current research on swarm intelligence algorithms and its applications. Including research and survey and application papers, this book serves as a platform for students and scholars interested in achieving their studies on swarm intelligence algorithms and their applications.
Book Synopsis Handbook of Research on Fireworks Algorithms and Swarm Intelligence by : Tan, Ying
Download or read book Handbook of Research on Fireworks Algorithms and Swarm Intelligence written by Tan, Ying and published by IGI Global. This book was released on 2019-12-27 with total page 471 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years, swarm intelligence has become a popular computational approach among researchers working on optimization problems throughout the globe. Several algorithms inside swarm intelligence have been implemented due to their application to real-world issues and other advantages. A specific procedure, Fireworks Algorithm, is an emerging method that studies the explosion process of fireworks within local areas. Applications of this developing program are undiscovered, and research is necessary for scientists to fully understand the workings of this innovative system. The Handbook of Research on Fireworks Algorithms and Swarm Intelligence is a pivotal reference source that provides vital research on theory analysis, improvements, and applications of fireworks algorithm. While highlighting topics such as convergence rate, parameter applications, and global optimization analysis, this publication explores up-to-date progress on the specific techniques of this algorithm. This book is ideally designed for researchers, data scientists, mathematicians, engineers, software developers, postgraduates, and academicians seeking coverage on this evolutionary computation method.
Book Synopsis Swarm Intelligence and Bio-Inspired Computation by : Xin-She Yang
Download or read book Swarm Intelligence and Bio-Inspired Computation written by Xin-She Yang and published by Newnes. This book was released on 2013-05-16 with total page 445 pages. Available in PDF, EPUB and Kindle. Book excerpt: Swarm Intelligence and bio-inspired computation have become increasing popular in the last two decades. Bio-inspired algorithms such as ant colony algorithms, bat algorithms, bee algorithms, firefly algorithms, cuckoo search and particle swarm optimization have been applied in almost every area of science and engineering with a dramatic increase of number of relevant publications. This book reviews the latest developments in swarm intelligence and bio-inspired computation from both the theory and application side, providing a complete resource that analyzes and discusses the latest and future trends in research directions. It can help new researchers to carry out timely research and inspire readers to develop new algorithms. With its impressive breadth and depth, this book will be useful for advanced undergraduate students, PhD students and lecturers in computer science, engineering and science as well as researchers and engineers. Focuses on the introduction and analysis of key algorithms Includes case studies for real-world applications Contains a balance of theory and applications, so readers who are interested in either algorithm or applications will all benefit from this timely book.
Book Synopsis Innovations in Swarm Intelligence by : Chee Peng Lim
Download or read book Innovations in Swarm Intelligence written by Chee Peng Lim and published by Springer Science & Business Media. This book was released on 2009-09-28 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the past two decades, swarm intelligence has emerged as a powerful approach to solving optimization as well as other complex problems. Swarm intelligence models are inspired by social behaviours of simple agents interacting among themselves as well as with the environment, e.g., flocking of birds, schooling of fish, foraging of bees and ants. The collective behaviours that emerge out of the interactions at the colony level are useful in achieving complex goals. The main aim of this research book is to present a sample of recent innovations and advances in techniques and applications of swarm intelligence. Among the topics covered in this book include: particle swarm optimization and hybrid methods, ant colony optimization and hybrid methods, bee colony optimization, glowworm swarm optimization, and complex social swarms, application of various swarm intelligence models to operational planning of energy plants, modeling and control of nanorobots, classification of documents, identification of disease biomarkers, and prediction of gene signals. The book is directed to researchers, practicing professionals, and undergraduate as well as graduate students of all disciplines who are interested in enhancing their knowledge in techniques and applications of swarm intelligence.
Book Synopsis New Advancements in Swarm Algorithms: Operators and Applications by : Erik Cuevas
Download or read book New Advancements in Swarm Algorithms: Operators and Applications written by Erik Cuevas and published by Springer. This book was released on 2019-04-02 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents advances in alternative swarm development that have proved to be effective in several complex problems. Swarm intelligence (SI) is a problem-solving methodology that results from the cooperation between a set of agents with similar characteristics. The study of biological entities, such as animals and insects, manifesting social behavior has resulted in several computational models of swarm intelligence. While there are numerous books addressing the most widely known swarm methods, namely ant colony algorithms and particle swarm optimization, those discussing new alternative approaches are rare. The focus on developments based on the simple modification of popular swarm methods overlooks the opportunity to discover new techniques and procedures that can be useful in solving problems formulated by the academic and industrial communities. Presenting various novel swarm methods and their practical applications, the book helps researchers, lecturers, engineers and practitioners solve their own optimization problems.
Book Synopsis Advances in Swarm Intelligence by : Anupam Biswas
Download or read book Advances in Swarm Intelligence written by Anupam Biswas and published by Springer Nature. This book was released on 2022-10-01 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: Swarm Intelligence (SI) has grown significantly, both from the perspective of algorithmic development and applications covering almost all disciplines science and technology. This book emphasizes the studies of existing SI techniques, their variants and applications. The book also contains reviews of new developments in SI techniques and hybridizations. Algorithm specific studies covering basic introduction and analysis of key components of these algorithms, such as convergence, balance of solution accuracy, computational costs, tuning and control of parameters. Application specific studies incorporating the ways of designing objective functions, solution representation and constraint handling. The book also includes studies on application domain specific adaptations in the SI techniques. The book will be beneficial for academicians and researchers from various disciplines of engineering and science working in applications of SI and other optimization problems.
Book Synopsis Membrane Computing for Distributed Control of Robotic Swarms: Emerging Research and Opportunities by : Florea, Andrei George
Download or read book Membrane Computing for Distributed Control of Robotic Swarms: Emerging Research and Opportunities written by Florea, Andrei George and published by IGI Global. This book was released on 2017-03-10 with total page 134 pages. Available in PDF, EPUB and Kindle. Book excerpt: Developments in bio-inspired computation have impacted multiple fields and created opportunities for new applications. In recent years, these techniques have been increasingly integrated into robotic systems. Membrane Computing for Distributed Control of Robotic Swarms: Emerging Research and Opportunities is an innovative reference source for the latest perspectives on biologically-inspired computation techniques for robot design and control. Highlighting a range of pivotal topics such as software engineering, simulation tools, and robotic security, this book is ideally designed for researchers, academics, students, and practitioners interested in the role of membrane computing in mobile robots.
Book Synopsis Recent Trends in Swarm Intelligence Enabled Research for Engineering Applications by : Siddhartha Bhattacharyya
Download or read book Recent Trends in Swarm Intelligence Enabled Research for Engineering Applications written by Siddhartha Bhattacharyya and published by Elsevier. This book was released on 2024-07-13 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the advent of data-intensive applications, the elimination of redundancy in disseminated information has become a serious challenge for researchers who are on the lookout for evolving metaheuristic algorithms which can explore and exploit the information feature space to derive the optimal settings for specific applications. Swarm intelligence algorithms have developed as one of the most widely used metaheuristic techniques for addressing this challenge in an effective way. Inspired by the behavior of a swarm of bees, these swarm intelligence techniques emulate the corresponding natural instincts to derive optimal solutions for data-intensive applications. Recent Trends in Swarm Intelligence Enabled Research for Engineering Applications focuses on the recent and most up-to-date technologies combining other intelligent tools with swarm intelligence techniques to yield robust and failsafe solutions to real world problems. This book aims to provide audiences with a platform to learn and gain insights into the latest developments in hybrid swarm intelligence. It will be useful to researchers, engineers, developers, practitioners, and graduate students working in the major and interdisciplinary areas of computational intelligence, communication systems, computer networks, and soft computing. Introduces the theory underpinning hybrid swarm intelligence-enabled research as well as the leading applications across the fields of communication, networking, and information engineering Presents a range of applications research, including signal processing, communication engineering, bioinformatics, controllers, federated learning systems, blockchain, and IoT Includes case studies and code snippets in applications chapters
Book Synopsis Nature-Inspired Computation and Swarm Intelligence by : Xin-She Yang
Download or read book Nature-Inspired Computation and Swarm Intelligence written by Xin-She Yang and published by Academic Press. This book was released on 2020-04-09 with total page 444 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nature-inspired computation and swarm intelligence have become popular and effective tools for solving problems in optimization, computational intelligence, soft computing and data science. Recently, the literature in the field has expanded rapidly, with new algorithms and applications emerging. Nature-Inspired Computation and Swarm Intelligence: Algorithms, Theory and Applications is a timely reference giving a comprehensive review of relevant state-of-the-art developments in algorithms, theory and applications of nature-inspired algorithms and swarm intelligence. It reviews and documents the new developments, focusing on nature-inspired algorithms and their theoretical analysis, as well as providing a guide to their implementation. The book includes case studies of diverse real-world applications, balancing explanation of the theory with practical implementation. Nature-Inspired Computation and Swarm Intelligence: Algorithms, Theory and Applications is suitable for researchers and graduate students in computer science, engineering, data science, and management science, who want a comprehensive review of algorithms, theory and implementation within the fields of nature inspired computation and swarm intelligence. Introduces nature-inspired algorithms and their fundamentals, including: particle swarm optimization, bat algorithm, cuckoo search, firefly algorithm, flower pollination algorithm, differential evolution and genetic algorithms as well as multi-objective optimization algorithms and others Provides a theoretical foundation and analyses of algorithms, including: statistical theory and Markov chain theory on the convergence and stability of algorithms, dynamical system theory, benchmarking of optimization, no-free-lunch theorems, and a generalized mathematical framework Includes a diversity of case studies of real-world applications: feature selection, clustering and classification, tuning of restricted Boltzmann machines, travelling salesman problem, classification of white blood cells, music generation by artificial intelligence, swarm robots, neural networks, engineering designs and others
Book Synopsis GPU-based Parallel Implementation of Swarm Intelligence Algorithms by : Ying Tan
Download or read book GPU-based Parallel Implementation of Swarm Intelligence Algorithms written by Ying Tan and published by Morgan Kaufmann. This book was released on 2016-04-15 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: GPU-based Parallel Implementation of Swarm Intelligence Algorithms combines and covers two emerging areas attracting increased attention and applications: graphics processing units (GPUs) for general-purpose computing (GPGPU) and swarm intelligence. This book not only presents GPGPU in adequate detail, but also includes guidance on the appropriate implementation of swarm intelligence algorithms on the GPU platform. GPU-based implementations of several typical swarm intelligence algorithms such as PSO, FWA, GA, DE, and ACO are presented and having described the implementation details including parallel models, implementation considerations as well as performance metrics are discussed. Finally, several typical applications of GPU-based swarm intelligence algorithms are presented. This valuable reference book provides a unique perspective not possible by studying either GPGPU or swarm intelligence alone. This book gives a complete and whole picture for interested readers and new comers who will find many implementation algorithms in the book suitable for immediate use in their projects. Additionally, some algorithms can also be used as a starting point for further research. Presents a concise but sufficient introduction to general-purpose GPU computing which can help the layman become familiar with this emerging computing technique Describes implementation details, such as parallel models and performance metrics, so readers can easily utilize the techniques to accelerate their algorithmic programs Appeals to readers from the domain of high performance computing (HPC) who will find the relatively young research domain of swarm intelligence very interesting Includes many real-world applications, which can be of great help in deciding whether or not swarm intelligence algorithms or GPGPU is appropriate for the task at hand
Book Synopsis Swarm Intelligence and Evolutionary Computation by : Georgios Kouziokas
Download or read book Swarm Intelligence and Evolutionary Computation written by Georgios Kouziokas and published by CRC Press. This book was released on 2023-03-07 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: The aim of this book is to present and analyse theoretical advances and also emerging practical applications of swarm and evolutionary intelligence. It comprises nine chapters. Chapter 1 provides a theoretical introduction of the computational optimization techniques regarding the gradient-based methods such as steepest descent, conjugate gradient, newton and quasi-Newton methods and also the non-gradient methods such as genetic algorithm and swarm intelligence algorithms. Chapter 2, discusses evolutionary computation techniques and genetic algorithm. Swarm intelligence theory and particle swarm optimization algorithm are reviewed in Chapter 3. Also, several variations of particle swarm optimization algorithm are analysed and explained such as Geometric PSO, PSO with mutation, Chaotic PSO with mutation, multi-objective PSO and Quantum mechanics – based PSO algorithm. Chapter 4 deals with two essential colony bio-inspired algorithms: Ant colony optimization (ACO) and Artificial bee colony (ABC). Chapter 5, presents and analyses Cuckoo search and Bat swarm algorithms and their latest variations. In chapter 6, several other metaheuristic algorithms are discussed such as: Firefly algorithm (FA), Harmony search (HS), Cat swarm optimization (CSO) and their improved algorithm modifications. The latest Bio-Inspired Swarm Algorithms are discussed in chapter 7, such as: Grey Wolf Optimization (GWO) Algorithm, Whale Optimization Algorithm (WOA), Grasshopper Optimization Algorithm (GOA) and other algorithm variations such as binary and chaotic versions. Chapter 8 presents machine learning applications of swarm and evolutionary algorithms. Illustrative real-world examples are presented with real datasets regarding neural network optimization and feature selection, using: genetic algorithm, Geometric PSO, Chaotic Harmony Search, Chaotic Cuckoo Search, and Evolutionary Algorithm and also crime forecasting using swarm optimized SVM. In chapter 9, applications of swarm intelligence on deep long short-term memory (LSTM) networks and Deep Convolutional Neural Networks (CNNs) are discussed, including LSTM hyperparameter tuning and Covid19 diagnosis from chest X-Ray images. The aim of the book is to present and discuss several state-of-theart swarm intelligence and evolutionary algorithms together with their variances and also several illustrative applications on machine learning and deep learning.
