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Evolution in Signal Processing and Telecommunication Networks: Proceedings of Sixth International Conference on Microelectronics, Electromagnetics and Telecommunications (ICMEET 2021), Volume 2 (Lecture Notes in Electrical Engineering #839)
by Suresh Chandra Satapathy Vikrant Bhateja P. Satish Rama Chowdary Jaume AngueraThis book discusses the latest developments and outlines future trends in the fields of microelectronics, electromagnetics and telecommunication. It contains original research works presented at the International Conference on Microelectronics, Electromagnetics and Telecommunication (ICMEET 2021), held in Bhubaneswar, Odisha, India during 27–28 August, 2021. The papers were written by scientists, research scholars and practitioners from leading universities, engineering colleges and R&D institutes from all over the world and share the latest breakthroughs in and promising solutions to the most important issues facing today’s society.
Evolution of Air Interface Towards 5G
by Suvra Sekhar DasOver the past few decades, wireless access networks have evolved extensively to support the tremendous growth of consumer traffic. This superlative growth of data consumption has come about due to several reasons, such as evolution of the consumer devices, the types of telephone and smartphone being used, convergence of services, digitisation of economic transactions, tele-education, telemedicine, m-commerce, virtual reality office, social media, e-governance, e-security, to name but a few.Not only has the society transformed to a digital world, but also the expectations from the services provided have increased many folds. The last mile/meters of delivery of all e-services is now required to be wireless. It has always been known that wireless links are the bottleneck to providing high data rates and high quality of service. Several wireless signalling and performance analysis techniques to overcome the hurdles of wireless channels have been developed over the last decade, and these are fuelling the evolution of 4G towards 5G. Evolution of Air Interface Towards 5G attempts to bring out some of the important developments that are contributing towards such growth.
Evolution of Cyber Technologies and Operations to 2035
by Misty BlowersThis book explores the future of cyber technologies and cyber operations which will influence advances in social media, cyber security, cyber physical systems, ethics, law, media, economics, infrastructure, military operations and other elements of societal interaction in the upcoming decades. It provides a review of future disruptive technologies and innovations in cyber security. It also serves as a resource for wargame planning and provides a strategic vision of the future direction of cyber operations. It informs military strategist about the future of cyber warfare. Written by leading experts in the field, chapters explore how future technical innovations vastly increase the interconnectivity of our physical and social systems and the growing need for resiliency in this vast and dynamic cyber infrastructure. The future of social media, autonomy, stateless finance, quantum information systems, the internet of things, the dark web, space satellite operations, and global network connectivity is explored along with the transformation of the legal and ethical considerations which surround them. The international challenges of cyber alliances, capabilities, and interoperability is challenged with the growing need for new laws, international oversight, and regulation which informs cybersecurity studies. The authors have a multi-disciplinary scope arranged in a big-picture framework, allowing both deep exploration of important topics and high level understanding of the topic. Evolution of Cyber Technologies and Operations to 2035 is as an excellent reference for professionals and researchers working in the security field, or as government and military workers, economics, law and more. Students will also find this book useful as a reference guide or secondary text book.
Evolution of Digitized Societies Through Advanced Technologies (Advanced Technologies and Societal Change)
by Arindam Biswas T. P. Singh Amitava Choudhury Mrinal AnandThis book provides an understanding of the evolution of digitization in our day to day life and how it has become a part of our social system. The obvious challenges faced during this process and how these challenges were overcome have been discussed. The discussions revolve around the solutions to these challenges by leveraging the use of various advanced technologies. The book mainly covers the use of these technologies in variety of areas such as smart cities, healthcare informatics, transportation automation, digital transformation of education. The book intends to be treated as a source to provide the systematic discussion to the bouquet of areas that are essential part of digitized societies. In light of this, the book accommodates theoretical, methodological, well-established, and validated empirical work dealing with various related topics.
Evolution of STEM-Driven Computer Science Education: The Perspective of Big Concepts
by Vytautas Štuikys Renata BurbaitėThe book discusses the evolution of STEM-driven Computer Science (CS) Education based on three categories of Big Concepts, Smart Education (Pedagogy), Technology (tools and adequate processes) and Content that relates to IoT, Data Science and AI. For developing, designing, testing, delivering and assessing learning outcomes for K-12 students (9-12 classes), the multi-dimensional modelling methodology is at the centre. The methodology covers conceptual and feature-based modelling, prototyping, and virtual and physical modelling at the implementation and usage level. Chapters contain case studies to assist understanding and learning. The book contains multiple methodological and scientific innovations including models, frameworks and approaches to drive STEM-driven CS education evolution.Educational strategists, educators, and researchers will find valuable material in this book to help them improve STEM-driven CS education strategies, curriculum development, and new ideas for research.
Evolution of Semantic Systems
by Bernd-Olaf Küppers Stefan Artmann Udo HahnComplex systems in nature and society make use of information for the development of their internal organization and the control of their functional mechanisms. Alongside technical aspects of storing, transmitting and processing information, the various semantic aspects of information, such as meaning, sense, reference and function, play a decisive part in the analysis of such systems. With the aim of fostering a better understanding of semantic systems from an evolutionary and multidisciplinary perspective, this volume collects contributions by philosophers and natural scientists, linguists, information and computer scientists. They do not follow a single research paradigm; rather they shed, in a complementary way, new light upon some of the most important aspects of the evolution of semantic systems. Evolution of Semantic Systems is intended for researchers in philosophy, computer science, and the natural sciences who work on the analysis or development of semantic systems, ontologies, or similar complex information structures. In the eleven chapters, they will find a broad discussion of topics ranging from underlying universal principles to representation and processing aspects to paradigmatic examples.
Evolution of Smart Sensing Ecosystems with Tamper Evident Security
by Pawel Sniatala S.S. Iyengar Sanjeev Kaushik RamaniThis book presents an overview on security and privacy issues in dynamic sensor networks and Internet of Things (IoT) networks and provides a novel tamper evident technique to counter and defend against these security related issues. The mission of this book is to explain the evolution of techniques and strategies in securing information transfer and storage thus facilitating a digital transition towards the modern tamper evident systems. The goal is also to aid business organizations that are dependent on the analysis of the large volumes of generated data in securing and addressing the associated growing threat of attackers relentlessly waging attacks and the challenges in protecting the confidentiality, integrity and provenance of data. The book also provides a comprehensive insight into the secure communication techniques and tools that have evolved and the impact they have had in supporting and flourishing the business through the cyber era. This book also includes chapters that discuss the most primitive encryption schemes to the most recent use of homomorphism in ensuring the privacy of the data thus leveraging greater use of new technologies like cloud computing and others.
Evolution, Complexity and Artificial Life
by Stefano Cagnoni Marco Mirolli Marco VillaniEvolution and complexity characterize both biological and artificial life - by direct modeling of biological processes and the creation of populations of interacting entities from which complex behaviors can emerge and evolve. This edited book includes invited chapters from leading scientists in the fields of artificial life, complex systems, and evolutionary computing. The contributions identify both fundamental theoretical issues and state-of-the-art real-world applications. The book is intended for researchers and graduate students in the related domains.
Evolutionary Algorithms
by Alain Petrowski Sana Ben-HamidaEvolutionary algorithms are bio-inspired algorithms based on Darwin’s theory of evolution. They are expected to provide non-optimal but good quality solutions to problems whose resolution is impracticable by exact methods. In six chapters, this book presents the essential knowledge required to efficiently implement evolutionary algorithms. Chapter 1 describes a generic evolutionary algorithm as well as the basic operators that compose it. Chapter 2 is devoted to the solving of continuous optimization problems, without constraint. Three leading approaches are described and compared on a set of test functions. Chapter 3 considers continuous optimization problems with constraints. Various approaches suitable for evolutionary methods are presented. Chapter 4 is related to combinatorial optimization. It provides a catalog of variation operators to deal with order-based problems. Chapter 5 introduces the basic notions required to understand the issue of multi-objective optimization and a variety of approaches for its application. Finally, Chapter 6 describes different approaches of genetic programming able to evolve computer programs in the context of machine learning.
Evolutionary Algorithms and Metaheuristics in Civil Engineering and Construction Management
by Jorge Magalhães-Mendes David GreinerThis book focuses on civil and structural engineering and construction management applications. The contributions constitute modified, extended and improved versions of research presented at the minisymposium organized by the editors at the ECCOMAS conference on this topic in Barcelona 2014.
Evolutionary Algorithms and Neural Networks: Theory and Applications (Studies in Computational Intelligence #780)
by Seyedali MirjaliliThis book introduces readers to the fundamentals of artificial neural networks, with a special emphasis on evolutionary algorithms. At first, the book offers a literature review of several well-regarded evolutionary algorithms, including particle swarm and ant colony optimization, genetic algorithms and biogeography-based optimization. It then proposes evolutionary version of several types of neural networks such as feed forward neural networks, radial basis function networks, as well as recurrent neural networks and multi-later perceptron. Most of the challenges that have to be addressed when training artificial neural networks using evolutionary algorithms are discussed in detail. The book also demonstrates the application of the proposed algorithms for several purposes such as classification, clustering, approximation, and prediction problems. It provides a tutorial on how to design, adapt, and evaluate artificial neural networks as well, and includes source codes for most of the proposed techniques as supplementary materials.
Evolutionary Algorithms for Food Science and Technology
by Evelyne Lutton Alberto Tonda Nathalie PerrotResearchers and practitioners in food science and technology routinely face several challenges, related to sparseness and heterogeneity of data, as well as to the uncertainty in the measurements and the introduction of expert knowledge in the models. Evolutionary algorithms (EAs), stochastic optimization techniques loosely inspired by natural selection, can be effectively used to tackle these issues. In this book, we present a selection of case studies where EAs are adopted in real-world food applications, ranging from model learning to sensitivity analysis.
Evolutionary Algorithms for Mobile Ad Hoc Networks
by Yoann Pigné Grégoire Danoy Pascal Bouvry Bernabé Dorronsoro Patricia RuizDescribes how evolutionary algorithms (EAs) can be used to identify, model, and minimize day-to-day problems that arise for researchers in optimization and mobile networkingMobile ad hoc networks (MANETs), vehicular networks (VANETs), sensor networks (SNs), and hybrid networks--each of these require a designer's keen sense and knowledge of evolutionary algorithms in order to help with the common issues that plague professionals involved in optimization and mobile networking.This book introduces readers to both mobile ad hoc networks and evolutionary algorithms, presenting basic concepts as well as detailed descriptions of each. It demonstrates how metaheuristics and evolutionary algorithms (EAs) can be used to help provide low-cost operations in the optimization process--allowing designers to put some "intelligence" or sophistication into the design. It also offers efficient and accurate information on dissemination algorithms, topology management, and mobility models to address challenges in the field.Evolutionary Algorithms for Mobile Ad Hoc Networks:Instructs on how to identify, model, and optimize solutions to problems that arise in daily researchPresents complete and up-to-date surveys on topics like network and mobility simulatorsProvides sample problems along with solutions/descriptions used to solve each, with performance comparisonsCovers current, relevant issues in mobile networks, like energy use, broadcasting performance, device mobility, and moreEvolutionary Algorithms for Mobile Ad Hoc Networks is an ideal book for researchers and students involved in mobile networks, optimization, advanced search techniques, and multi-objective optimization.
Evolutionary Algorithms, Swarm Dynamics and Complex Networks
by Ivan Zelinka Guanrong ChenEvolutionary algorithms constitute a class of well-known algorithms, which are designed based on the Darwinian theory of evolution and Mendelian theory of heritage. They are partly based on random and partly based on deterministic principles. Due to this nature, it is challenging to predict and control its performance in solving complex nonlinear problems. Recently, the study of evolutionary dynamics is focused not only on the traditional investigations but also on the understanding and analyzing new principles, with the intention of controlling and utilizing their properties and performances toward more effective real-world applications. In this book, based on many years of intensive research of the authors, is proposing novel ideas about advancing evolutionary dynamics towards new phenomena including many new topics, even the dynamics of equivalent social networks. In fact, it includes more advanced complex networks and incorporates them with the CMLs (coupled map lattices), which are usually used for spatiotemporal complex systems simulation and analysis, based on the observation that chaos in CML can be controlled, so does evolution dynamics. All the chapter authors are, to the best of our knowledge, originators of the ideas mentioned above and researchers on evolutionary algorithms and chaotic dynamics as well as complex networks, who will provide benefits to the readers regarding modern scientific research on related subjects.
Evolutionary Approach to Machine Learning and Deep Neural Networks: Neuro-Evolution and Gene Regulatory Networks
by Hitoshi IbaThis book provides theoretical and practical knowledge about a methodology for evolutionary algorithm-based search strategy with the integration of several machine learning and deep learning techniques. These include convolutional neural networks, Gröbner bases, relevance vector machines, transfer learning, bagging and boosting methods, clustering techniques (affinity propagation), and belief networks, among others. The development of such tools contributes to better optimizing methodologies. Beginning with the essentials of evolutionary algorithms and covering interdisciplinary research topics, the contents of this book are valuable for different classes of readers: novice, intermediate, and also expert readers from related fields.Following the chapters on introduction and basic methods, Chapter 3 details a new research direction, i.e., neuro-evolution, an evolutionary method for the generation of deep neural networks, and also describes how evolutionary methods are extended in combination with machine learning techniques. Chapter 4 includes novel methods such as particle swarm optimization based on affinity propagation (PSOAP), and transfer learning for differential evolution (TRADE), another machine learning approach for extending differential evolution. The last chapter is dedicated to the state of the art in gene regulatory network (GRN) research as one of the most interesting and active research fields. The author describes an evolving reaction network, which expands the neuro-evolution methodology to produce a type of genetic network suitable for biochemical systems and has succeeded in designing genetic circuits in synthetic biology. The author also presents real-world GRN application to several artificial intelligent tasks, proposing a framework of motion generation by GRNs (MONGERN), which evolves GRNs to operate a real humanoid robot.
Evolutionary Artificial Intelligence: Proceedings of ICEAI 2023 (Algorithms for Intelligent Systems)
by Francisco M. Gonzalez-Longatt Przemyslaw Falkowski-Gilski R. Kanthavel David AsirvathamThis book gathers a collection of selected works and new research results of scholars and graduate students presented at International Conference on Evolutionary Artificial Intelligence (ICEAI 2023) held in Malaysia during 13-14 September 2023. The focus of the book is interdisciplinary in nature and includes research on all aspects of evolutionary computation to find effective solutions to a wide range of computationally difficult problems. The book covers topics such as particle swarm optimization, evolutionary programming, genetic programming, hybrid evolutionary algorithms, ant colony optimization, evolutionary neural networks, evolutionary reinforcement learning, genetic algorithms, memetic algorithms, novel bio-inspired algorithms, evolving multi-agent systems, agent-based evolutionary approaches, and evolutionary game theory.
Evolutionary Bioinformatics
by Donald R. ForsdykeNow in its third edition and supplemented with more online material, this book aims to make the "new" information-based (rather than gene-based) bioinformatics intelligible both to the "bio" people and the "info" people. Books on bioinformatics have traditionally served gene-hunters, and biologists who wish to construct family trees showing tidy lines of descent. While dealing extensively with the exciting topics of gene discovery and database-searching, such books have hardly considered genomes as information channels through which multiple forms and levels of information have passed through the generations. This "new bioinformatics" contrasts with the "old" gene-based bioinformatics that so preoccupies previous texts. Forms of information that we are familiar with (mental, textual) are related to forms with which we are less familiar (hereditary). The book extends a line of evolutionary thought that leads from the nineteenth century (Darwin, Butler, Romanes, Bateson), through the twentieth (Goldschmidt, White), and into the twenty first (the final works of the late Stephen Jay Gould). Long an area of controversy, diverging views may now be reconciled.
Evolutionary Biology
by Pierre PontarottiSince 1997, scientists of different disciplines sharing a deep interest in concepts and knowledge related to evolutionary biology have held the annual Evolutionary Biology Meetings in Marseille in order to discuss their research and promote collaboration. Lately scientists especially focusing on applications have also joined the group. This book starts with the report of the "12th Evolutionary Biology Meeting", which gives a general idea of the meeting's epistemological stance. This is followed by 22 chapters, a selection of the most representative contributions, which are grouped under the following four themes: Part I Concepts and Knowledge - Part II Modelization - Part III Applied Evolutionary Biology - Part IV Applications in Other Fields -Part IV transcends the field of biology, presenting applications of evolutionary biology in economics and astronomy.
Evolutionary Computation (International Series on Computational Intelligence)
by D. Dumitrescu Beatrice Lazzerini Lakhmi C. Jain A. DumitrescuRapid advances in evolutionary computation have opened up a world of applications-a world rapidly growing and evolving. Decision making, neural networks, pattern recognition, complex optimization/search tasks, scheduling, control, automated programming, and cellular automata applications all rely on evolutionary computation. Evolutionary Com
Evolutionary Computation 1: Basic Algorithms and Operators (Ieee Press Series On Computational Intelligence Ser. #1)
by Thomas Baeck D. B Fogel Z MichalewiczThe field of evolutionary computation is expanding dramatically, fueled by the vast investment that reflects the value of applying its techniques. Culling material from the Handbook of Evolutionary Computation, Evolutionary Computation 1: Basic Algorithms and Operators contains up-to-date information on algorithms and operators used in evolutionary computing. This volume discusses the basic ideas that underlie the main paradigms of evolutionary algorithms, evolution strategies, evolutionary programming, and genetic programming. It is intended to be used by individual researchers, teachers, and students working and studying in this expanding field.
Evolutionary Computation Techniques: A Comparative Perspective
by Erik Cuevas Diego Oliva Valentín OsunaThis book compares the performance of various evolutionary computation (EC) techniques when they are faced with complex optimization problems extracted from different engineering domains. Particularly focusing on recently developed algorithms, it is designed so that each chapter can be read independently. Several comparisons among EC techniques have been reported in the literature, however, they all suffer from one limitation: their conclusions are based on the performance of popular evolutionary approaches over a set of synthetic functions with exact solutions and well-known behaviors, without considering the application context or including recent developments. In each chapter, a complex engineering optimization problem is posed, and then a particular EC technique is presented as the best choice, according to its search characteristics. Lastly, a set of experiments is conducted in order to compare its performance to other popular EC methods.
Evolutionary Computation and Complex Networks
by Hussein A. Abbass Jing Liu Kay Chen TanThis book introduces the linkage between evolutionary computation and complex networks and the advantages of cross-fertilising ideas from both fields. Instead of introducing each field individually, the authors focus on the research that sits at the interface of both fields. The book is structured to address two questions: (1) how complex networks are used to analyze and improve the performance of evolutionary computation methods? (2) how evolutionary computation methods are used to solve problems in complex networks? The authors interweave complex networks and evolutionary computing, using evolutionary computation to discover community structure, while also using network analysis techniques to analyze the performance of evolutionary algorithms. The book is suitable for both beginners and senior researchers in the fields of evolutionary computation and complex networks.
Evolutionary Computation in Combinatorial Optimization
by Bin Hu Francisco Chicano Pablo García-SánchezThisbook constitutes the refereed proceedings of the 16th European Conference onEvolutionary Computation in Combinatorial Optimization, EvoCOP 2016, held in Porto,Portugal, in March/April 2016, co-located with the Evo*2015 events EuroGP,EvoMUSART and EvoApplications. The17 revised full papers presented were carefully reviewed and selected from 44submissions. The papers cover methodology, applications and theoretical studies. Themethods included evolutionary and memetic algorithms, variable neighborhoodsearch, particle swarm optimization, hyperheuristics, mat-heuristic and otheradaptive approaches. Applications included both traditional domains, such asgraph coloring, vehicle routing, the longest common subsequence problem, thequadratic assignment problem; and new(er) domains such as the traveling thiefproblem, web service location, and finding short addition chains. Thetheoretical studies involved fitness landscape analysis, local search and recombinationoperator analysis, and the big valley search space hypothesis. Theconsideration of multiple objectives, dynamic and noisy environments was alsopresent in a number of articles.
Evolutionary Computation in Combinatorial Optimization
by Bin Hu Manuel López-IbáñezThis book constitutes the refereed proceedings of the 16th European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2016, held in Porto, Portugal, in March/April 2016, co-located with the Evo*2015 events EuroGP, EvoMUSART and EvoApplications. The 17 revised full papers presented were carefully reviewed and selected from 44 submissions. The papers cover methodology, applications and theoretical studies. The methods included evolutionary and memetic algorithms, variable neighborhood search, particle swarm optimization, hyperheuristics, mat-heuristic and other adaptive approaches. Applications included both traditional domains, such as graph coloring, vehicle routing, the longest common subsequence problem, the quadratic assignment problem; and new(er) domains such as the traveling thief problem, web service location, and finding short addition chains. The theoretical studies involved fitness landscape analysis, local search and recombination operator analysis, and the big valley search space hypothesis. The consideration of multiple objectives, dynamic and noisy environments was also present in a number of articles.
Evolutionary Computation in Combinatorial Optimization
by Francisco Chicano Gabriela OchoaThis book constitutes the refereed proceedings of the 15th European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2015, held in Copenhagen, Denmark, in April 2015, co-located with the Evo*2015 events EuroGP, EvoMUSART and EvoApplications. The 19 revised full papers presented were carefully reviewed and selected from 46 submissions. The papers cover methodology, applications and theoretical studies. The methods included evolutionary and memetic (hybrid) algorithms, iterated local search, variable neighbourhood search, ant colony optimization, artificial immune systems, hyper-heuristics and other adaptive approaches. The applications include both traditional domains, such as graph coloring, knapsack, vehicle routing, job-shop scheduling, the p-median and the orienteering problems; and new(er) domains such as designing deep recurrent neural networks, detecting network community structure, lock scheduling of ships, cloud resource management, the fire-fighter problem and AI planning. The theoretical studies involved approximation ratio, runtime and black-box complexity analyses.