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Yoann Pigné Evolutionary Algorithms for - maz-32.ru
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Yoann Pigné Evolutionary Algorithms for Mobile Ad Hoc Networks


Describes how evolutionary algorithms (EAs) can be used to identify, model, and minimize day-to-day problems that arise for researchers in optimization and mobile networking Mobile 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 research Presents complete and up-to-date surveys on topics like network and mobility simulators Provides sample problems along with solutions/descriptions used to solve each, with performance comparisons Covers current, relevant issues in mobile networks, like energy use, broadcasting performance, device mobility, and more Evolutionary 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.

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Dan Simon Evolutionary Optimization Algorithms


A clear and lucid bottom-up approach to the basic principles of evolutionary algorithms Evolutionary algorithms (EAs) are a type of artificial intelligence. EAs are motivated by optimization processes that we observe in nature, such as natural selection, species migration, bird swarms, human culture, and ant colonies. This book discusses the theory, history, mathematics, and programming of evolutionary optimization algorithms. Featured algorithms include genetic algorithms, genetic programming, ant colony optimization, particle swarm optimization, differential evolution, biogeography-based optimization, and many others. Evolutionary Optimization Algorithms: Provides a straightforward, bottom-up approach that assists the reader in obtaining a clear—but theoretically rigorous—understanding of evolutionary algorithms, with an emphasis on implementation Gives a careful treatment of recently developed EAs—including opposition-based learning, artificial fish swarms, bacterial foraging, and many others— and discusses their similarities and differences from more well-established EAs Includes chapter-end problems plus a solutions manual available online for instructors Offers simple examples that provide the reader with an intuitive understanding of the theory Features source code for the examples available on the author's website Provides advanced mathematical techniques for analyzing EAs, including Markov modeling and dynamic system modeling Evolutionary Optimization Algorithms: Biologically Inspired and Population-Based Approaches to Computer Intelligence is an ideal text for advanced undergraduate students, graduate students, and professionals involved in engineering and computer science.

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Omid Bozorg-Haddad Meta-heuristic and Evolutionary Algorithms for Engineering Optimization


A detailed review of a wide range of meta-heuristic and evolutionary algorithms in a systematic manner and how they relate to engineering optimization problems This book introduces the main metaheuristic algorithms and their applications in optimization. It describes 20 leading meta-heuristic and evolutionary algorithms and presents discussions and assessments of their performance in solving optimization problems from several fields of engineering. The book features clear and concise principles and presents detailed descriptions of leading methods such as the pattern search (PS) algorithm, the genetic algorithm (GA), the simulated annealing (SA) algorithm, the Tabu search (TS) algorithm, the ant colony optimization (ACO), and the particle swarm optimization (PSO) technique. Chapter 1 of Meta-heuristic and Evolutionary Algorithms for Engineering Optimization provides an overview of optimization and defines it by presenting examples of optimization problems in different engineering domains. Chapter 2 presents an introduction to meta-heuristic and evolutionary algorithms and links them to engineering problems. Chapters 3 to 22 are each devoted to a separate algorithm— and they each start with a brief literature review of the development of the algorithm, and its applications to engineering problems. The principles, steps, and execution of the algorithms are described in detail, and a pseudo code of the algorithm is presented, which serves as a guideline for coding the algorithm to solve specific applications. This book: Introduces state-of-the-art metaheuristic algorithms and their applications to engineering optimization; Fills a gap in the current literature by compiling and explaining the various meta-heuristic and evolutionary algorithms in a clear and systematic manner; Provides a step-by-step presentation of each algorithm and guidelines for practical implementation and coding of algorithms; Discusses and assesses the performance of metaheuristic algorithms in multiple problems from many fields of engineering; Relates optimization algorithms to engineering problems employing a unifying approach. Meta-heuristic and Evolutionary Algorithms for Engineering Optimization is a reference intended for students, engineers, researchers, and instructors in the fields of industrial engineering, operations research, optimization/mathematics, engineering optimization, and computer science. OMID BOZORG-HADDAD, PhD, is Professor in the Department of Irrigation and Reclamation Engineering at the University of Tehran, Iran. MOHAMMAD SOLGI, M.Sc., is Teacher Assistant for M.Sc. courses at the University of Tehran, Iran. HUGO A. LOÁICIGA, PhD, is Professor in the Department of Geography at the University of California, Santa Barbara, United States of America.

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Hugo Kubinyi Evolutionary Algorithms in Molecular Design


When trying to find new methods and problem-solving strategies for their research, scientists often turn to nature for inspiration. An excellent example of this is the application of Darwin's Theory of Evolution, particularly the notion of the 'survival of the fittest', in computer programs designed to search for optimal solutions to many kinds of problems. These 'evolutionary algorithms' start from a population of possible solutions to a given problem and, by applying evolutionary principles, evolve successive generations with improved characteristics until an optimal, or near-optimal, solution is obtained. This book highlights the versatility of evolutionary algorithms in areas of relevance to molecular design with a particular focus on drug design. The authors, all of whom are experts in their field, discuss the application of these computational methods to a wide range of research problems including conformational analysis, chemometrics and quantitative structure-activity relationships, de novo molecular design, chemical structure handling, combinatorial library design, and the study of protein folding. In addition, the use of evolutionary algorithms in the determination of structures by X-ray crystallography and NMR spectroscopy is also covered. These state-of-the-art reviews, together with a discussion of new techniques and future developments in the field, make this book a truly valuable and highly up-to-date resource for anyone engaged in the application or development of computer-assisted methods in scientific research.

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Alain Petrowski Evolutionary Algorithms


Evolutionary 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.

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Evelyne Lutton Evolutionary Algorithms for Food Science and Technology


Researchers 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.

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Jie Liang Models and Algorithms for Biomolecules and Molecular Networks


By providing expositions to modeling principles, theories, computational solutions, and open problems, this reference presents a full scope on relevant biological phenomena, modeling frameworks, technical challenges, and algorithms. Up-to-date developments of structures of biomolecules, systems biology, advanced models, and algorithms Sampling techniques for estimating evolutionary rates and generating molecular structures Accurate computation of probability landscape of stochastic networks, solving discrete chemical master equations End-of-chapter exercises

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Ivan Stojmenovic Handbook of Applied Algorithms


Discover the benefits of applying algorithms to solve scientific, engineering, and practical problems Providing a combination of theory, algorithms, and simulations, Handbook of Applied Algorithms presents an all-encompassing treatment of applying algorithms and discrete mathematics to practical problems in «hot» application areas, such as computational biology, computational chemistry, wireless networks, and computer vision. In eighteen self-contained chapters, this timely book explores: * Localized algorithms that can be used in topology control for wireless ad-hoc or sensor networks * Bioinformatics algorithms for analyzing data * Clustering algorithms and identification of association rules in data mining * Applications of combinatorial algorithms and graph theory in chemistry and molecular biology * Optimizing the frequency planning of a GSM network using evolutionary algorithms * Algorithmic solutions and advances achieved through game theory Complete with exercises for readers to measure their comprehension of the material presented, Handbook of Applied Algorithms is a much-needed resource for researchers, practitioners, and students within computer science, life science, and engineering. Amiya Nayak, PhD, has over seventeen years of industrial experience and is Full Professor at the School of Information Technology and Engineering at the University of Ottawa, Canada. He is on the editorial board of several journals. Dr. Nayak's research interests are in the areas of fault tolerance, distributed systems/algorithms, and mobile ad-hoc networks. Ivan StojmenoviC?, PhD, is Professor at the University of Ottawa, Canada (www.site.uottawa.ca/~ivan), and Chair Professor of Applied Computing at the University of Birmingham, United Kingdom. Dr. Stojmenovic? received the Royal Society Wolfson Research Merit Award. His current research interests are mostly in the design and analysis of algorithms for wireless ad-hoc and sensor networks.

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Christian Blum Optimization Techniques for Solving Complex Problems


Real-world problems and modern optimization techniques to solve them Here, a team of international experts brings together core ideas for solving complex problems in optimization across a wide variety of real-world settings, including computer science, engineering, transportation, telecommunications, and bioinformatics. Part One—covers methodologies for complex problem solving including genetic programming, neural networks, genetic algorithms, hybrid evolutionary algorithms, and more. Part Two—delves into applications including DNA sequencing and reconstruction, location of antennae in telecommunication networks, metaheuristics, FPGAs, problems arising in telecommunication networks, image processing, time series prediction, and more. All chapters contain examples that illustrate the applications themselves as well as the actual performance of the algorithms.?Optimization Techniques for Solving Complex Problems is a valuable resource for practitioners and researchers who work with optimization in real-world settings.

14260.21 RUR

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Harding Jenny A. Evolutionary Computing in Advanced Manufacturing


This cutting-edge book covers emerging, evolutionary and nature inspired optimization techniques in the field of advanced manufacturing. The complexity of real life advanced manufacturing problems often cannot be solved by traditional engineering or computational methods. Hence, in recent years researchers and practitioners have proposed and developed new strands of advanced, intelligent techniques and methodologies. Evolutionary computing approaches are introduced in the context of a wide range of manufacturing activities, and through the examination of practical problems and their solutions, readers will gain confidence to apply these powerful computing solutions. The initial chapters introduce and discuss the well established evolutionary algorithm, to help readers to understand the basic building blocks and steps required to successfully implement their own solutions to real life advanced manufacturing problems. In the later chapters, modified and improved versions of evolutionary algorithms are discussed. The book concludes with appendices which provide general descriptions of several evolutionary algorithms.

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Evolutionary Algorithms for Mobile Ad Hoc Networks Nature ...

Evolutionary Algorithms for Mobile Ad Hoc Networks Nature Inspired Computing Series: Amazon.de: Dorronsoro, Bernabé, Ruiz, Patricia, Danoy, Grégoire, Pigné, Yoann ...

Wiley: Evolutionary Algorithms for Mobile Ad Hoc Networks ...

Evolutionary Algorithms for Mobile Ad Hoc Networks is an ideal book for researchers and students involved in mobile networks, optimization, ... YOANN PIGNÉ, PHD, obtained his PhD from the University of Le Havre, France, on Modelling and Processing Dynamic Graphs, Applications to Mobile Ad Hoc Networks. PASCAL BOUVRY, PHD, earned his PhD in computer science from the University of Grenoble ...

Evolutionary Algorithms for Mobile Ad Hoc Networks | Wiley ...

des Mines) on the optimization of real-world problems using co-evolutionary genetic algorithms, including topology management problems in mobile ad hoc networks. YOANN PIGNÉ, PHD,obtained his PhD from the University of Le Havre, France, on Modelling and Processing Dynamic Graphs, Applications to Mobile

Evolutionary Algorithms for Mobile Ad Hoc Networks (Nature ...

Evolutionary Algorithms for Mobile Ad Hoc Networks (Nature-Inspired Computing Series) [Dorronsoro, Bernabé, Ruiz, Patricia, Danoy, Grégoire, Pigné, Yoann, Bouvry, Pascal] on Amazon.com. *FREE* shipping on qualifying offers. Evolutionary Algorithms for Mobile Ad Hoc Networks (Nature-Inspired Computing Series)

Nature Inspired Computing Series: Evolutionary Algorithms ...

YOANN PIGNÉ, PHD, obtained his PhDfrom the University of Le Havre, France, on Modelling andProcessing Dynamic Graphs, Applications to Mobile Ad HocNetworks. PASCAL BOUVRY, PHD, earned his PhD incomputer science from the University of Grenoble (INPG), France, in1994.

· Yoann Pigné

Publications 2019. Journal Article Yoann Pigné, Tomás Navarrete Gutiérrez, Thomas Gibon, Thomas Schaubroeck, Emil Popovici, Allan Hayato Shimako, Enrico Benetto, Ligia Tiruta-Barna, "A tool to operationalize dynamic LCA, including time differentiation on the complete background database", In The International Journal of Life Cycle Assessment, DOI: 10.1007/s11367-019-01696-6, 2019.

Evolutionary Algorithms for Mobile Ad Hoc Networks ...

Evolutionary Algorithms for Mobile Ad Hoc Networks: Dorronsoro, Bernabé, Ruiz, Patricia, Danoy, Grégoire, Pigné, Yoann, Bouvry, Pascal: Amazon.nl

· Yoann Pigné

Journal Article Yoann Pigné, Tomás Navarrete Gutiérrez, Thomas Gibon, Thomas Schaubroeck, Emil Popovici, Allan Hayato Shimako, Enrico Benetto, Ligia Tiruta-Barna, "A tool to operationalize dynamic LCA, including time differentiation on the complete background database", In The International Journal of Life Cycle Assessment, Volume 25, Issue 2, Pages 267-279.

Introduction to Evolutionary Algorithms - Evolutionary ...

This chapter focuses on the class of approximate methods, and more precisely evolutionary algorithms (EAs), which are population‐based metaheuristics able to obtain acceptable solutions in reasonable time. However, based on the famous “no free lunch theorem”, none of these algorithms will outperform all the others on all classes of problems. The chapter provides some introduction of ...

INTRODUCTION TO MOBILE AD HOC NETWORKS

Evolutionary Algorithms for Mobile Ad Hoc Networks, First Edition. Bernabé Dorronsoro, Bernabé Dorronsoro, Patricia Ruiz, Grégoire Danoy, Yoann Pigné, and Pascal Bouvry.

Evolutionary Algorithms for Mobile Ad Hoc Networks Nature ...

Evolutionary Algorithms for Mobile Ad Hoc Networks: Instructs on how to identify, model, and optimize solutions to problems that arise in daily research Presents complete and up-to-date surveys on topics like network and mobility simulators Provides sample problems along with solutions/descriptions used to solve each, with performance comparisons Covers current, relevant issues in mobile ...

[0803.2314] Problem Solving and Complex Systems

Computer Science > Neural and Evolutionary Computing. Title: Problem Solving and Complex Systems. Authors: Frédéric Guinand (LITIS), Yoann Pigné (LITIS) (Submitted on 15 Mar 2008) Abstract: The observation and modeling of natural Complex Systems (CSs) like the human nervous system, the evolution or the weather, allows the definition of special abilities and models reusable to solve other ...

Evolutionary Algorithms for Mobile Ad Hoc Networks (eBook ...

Evolutionary Algorithms for Mobile Ad Hoc Networks (eBook) by grégoire danoy, yoann pigné, Pascal Bouvry, bernabé dorronsoro, Patricia Ruiz (Author), isbn:9781118832028, synopsis:Describes how evolutionary algorithms (EAs) can...

Evolutionary Algorithms for Mobile Ad Hoc Networks von ...

Jetzt online bestellen! Heimlieferung oder in Filiale: Evolutionary Algorithms for Mobile Ad Hoc Networks von Patricia Ruiz, Bernabé Dorronsoro, Grégoire Danoy, Pascal Bouvry, Yoann Pigné | Orell Füssli: Der Buchhändler Ihres Vertrauens

‎Evolutionary Algorithms for Mobile Ad Hoc Networks on ...

Evolutionary Algorithms for Mobile Ad Hoc Networks: ... More Books by Bernabe Dorronsoro, Patricia Ruiz, Grégoire Danoy, Yoann Pigné & Pascal Bouvry See All. Optimization and Learning. 2020 Advances in Artificial Intelligence. 2015 Cellular Genetic Algorithms. 2009 Other Books in This Series See All . Wireless Computing in Medicine. 2016 More ways to shop: Find an Apple Store or other ...

Books by Yoann Pigné

Books listed by ISBN > Wiley > Yoann Pigné. Yoann Pigné. title ISBN-13 (ISBN-10) year of publica-tion other author(s) Evolutionary Algorithms for Mobile Ad Hoc Networks: 978-1-118-34113-1 (1-118-34113-9) 2014: Bernabé Dorronsoro · Patricia Ruiz · Grégoire Danoy · Pascal Bouvry: Yoann Poilane. Oh the playing played! darn! drat! weaving sweeping trick. Mexico plays soon ...

Nature Inspired Computing Series - Evolutionary Algorithms ...

Describes how evolutionary algorithms (EAs) can be used toidentify, model, and minimize day-to-day problems that arise forresearchers in optimization and mobile networkingMobile ad hoc networks (MANETs), vehicular networks (VANETs),sensor networks (SNs), and hybrid networks--each of theserequire a designer's keen sense and knowledge of evolutionaryalgorithms in order to help with the common ...

Evolutionary Algorithms for Mobile Ad Hoc Networks ...

Bernabé Dorronsoro, Patricia Ruiz, Grégoire Danoy, Yoann Pigné, Pascal Bouvry. This comprehensive guide describes how evolutionary algorithms (EA) may be used to identify, model, and optimize day-to-day problems that arise for researchers in optimization and mobile networking. It provides efficient and accurate information on dissemination algorithms, topology management, and mobility ...

Thumbnail image - download.e-bookshelf.de

Evolutionary algorithms for mobile ad hoc networks / Bernabé Dorronsoro, Patricia Ruiz, Grégoire Danoy, Yoann Pigné, Pascal Bouvry. pages cm. – (Nature-inspired computing series) Includes bibliographical references. ISBN 978-1-118-34113-1 (hardback) 1. Mobile communication systems. 2. Evolutionary computation. 3. Genetic algorithms. I. Title.

Evolutionary Algorithms for Mobile Ad Hoc Networks ...

Evolutionary Algorithms for Mobile Ad Hoc Networks: Dorronsoro, Bernabé, Ruiz, Patricia, Danoy, Grégoire, Pigné, Yoann, Bouvry, Pascal: 0001118341139: Books ...

Nature-Inspired Computing Ser.: Evolutionary Algorithms ...

Find many great new & used options and get the best deals for Nature-Inspired Computing Ser.: Evolutionary Algorithms for Mobile Ad Hoc Networks by Grégoire Danoy, Patricia Ruiz, Pascal Bouvry, Bernabé Dorronsoro and Yoann Pigné (2014, Hardcover) at the best online prices at eBay! Free shipping for many products!

Evolutionary Algorithms for Mobile Ad Hoc Networks - CORE

Evolutionary Algorithms for Mobile Ad Hoc Networks . By Bernabé Dorronsoro, Patricia Ruiz, Grégoire Danoy, Yoann Pigné and Pascal Bouvry. Topics: Engineering, computing & technology :: Computer science [C05], Ingénierie, informatique & technologie :: Sciences informatiques [C05 ...

Yoann Pigné's research works | Université du Havre, Le ...

Yoann Pigné's 32 research works with 395 citations and 6,763 reads, including: A tool to operationalize dynamic LCA, including time differentiation on the complete background database

Evolutionary Algorithms for Mobile Ad Hoc Networks - ebook ...

Evolutionary Algorithms for Mobile Ad Hoc Networks, Patricia Ruiz, Pascal Bouvry, Bernabé Dorronsoro, Grégoire Danoy, Yoann Pigné, Wiley. Des milliers de livres avec la livraison chez vous en 1 jour ou en magasin avec -5% de réduction .

Evolutionary Algorithms for Mobile Ad Hoc Networks (Nature ...

Evolutionary Algorithms for Mobile Ad Hoc Networks (Nature-Inspired Computing Series) by Bernabé Dorronsoro (2014-04-28): Bernabé Dorronsoro; Patricia Ruiz; Grégoire Danoy; Yoann Pigné; Pascal Bouvry;: Books - Amazon.ca

‪Yoann Pigné‬ - ‪Google Scholar‬

‪Researcher in computer science, University of Le Havre, France‬ - ‪Cited by 584‬ - ‪Mobile Networks‬ - ‪vehicular Traffic‬ - ‪Dynamic Graphs‬

Amazon.fr - Evolutionary Algorithms for Mobile Ad Hoc ...

Retrouvez Evolutionary Algorithms for Mobile Ad Hoc Networks et des millions de livres en stock sur Amazon.fr. Achetez neuf ou d'occasion Amazon.fr - Evolutionary Algorithms for Mobile Ad Hoc Networks - Dorronsoro, Bernabé, Ruiz, Patricia, Danoy, Grégoire, Pigné, Yoann, Bouvry, Pascal - Livres

Problem Solving and Complex Systems - CORE

By Frédéric Guinand and Yoann Pigné. Abstract. The observation and modeling of natural Complex Systems (CSs) like the human nervous system, the evolution or the weather, allows the definition of special abilities and models reusable to solve other problems. For instance, Genetic Algorithms or Ant Colony Optimizations are inspired from natural CSs to solve optimization problems. This paper ...

EvoAPPS – EvoStar 2021

Yoann Pigné, LITIS – Université Le Havre Normandie Clara Pizzuti, CNR-ICAR Petr Pošík, Czech Technical University in Prague Arkadiusz Poteralski, Silesian University of Technology Raneem Qaddoura, Philadelphia University José Carlos Ribeiro, Polytechnic Institute of Leiria Sebastian Risi, IT University of Copenhagen

An Ant-Based Model for Multiple Sequence Alignment ...

Yoann Pigné; Conference paper. 2 Citations; 1.1k Downloads; Part of the Lecture Notes in Computer Science book series (LNCS, volume 4818) Abstract. Multiple sequence alignment is a key process in today’s biology, and finding a relevant alignment of several sequences is much more challenging than just optimizing some improbable evaluation functions. Our approach for addressing multiple ...

Evolutionary Algorithms for Mobile Ad Hoc Networks von ...

Jetzt online bestellen! Heimlieferung oder in Filiale: Evolutionary Algorithms for Mobile Ad Hoc Networks von Bernabé Dorronsoro, Patricia Ruiz, Grégoire Danoy, Yoann Pigné, Pascal Bouvry | Orell Füssli: Der Buchhändler Ihres Vertrauens

Evolutionary Algorithms for Mobile Ad Hoc Networks eBook ...

Evolutionary Algorithms for Mobile Ad Hoc Networks. by Patricia Ruiz,Pascal Bouvry,Bernabé Dorronsoro,Grégoire Danoy,Yoann Pigné. Nature-Inspired Computing Series . Thanks for Sharing! You submitted the following rating and review. We'll publish them on our site once we've reviewed them.

[0803.2092] An Ant-Based Model for Multiple Sequence Alignment

Authors: Frédéric Guinand (LITIS), Yoann Pigné (LITIS) (Submitted on 14 Mar 2008) Abstract: Multiple sequence alignment is a key process in today's biology, and finding a relevant alignment of several sequences is much more challenging than just optimizing some improbable evaluation functions. Our approach for addressing multiple sequence alignment focuses on the building of structures in a ...

Evolutionary Algorithms for Mobile Ad Hoc Networks Nature ...

Evolutionary Algorithms for Mobile Ad Hoc Networks Nature-Inspired Computing Series by Bernabé Dorronsoro 2014-04-28: Amazon.es: Bernabé Dorronsoro; Patricia Ruiz; Grégoire Danoy; Yoann Pigné; Pascal Bouvry;: Libros

Sensitivity analysis for a realistic vehicular mobility ...

Relevance estimation and value calibration of evolutionary algorithm parameters. In Proceedings of the 20th international joint conference on Artifical intelligence, pages 975--980, San Francisco, CA, USA, 2007. Morgan Kaufmann Publishers Inc. Google Scholar Digital Library; V. Naumov, R. Baumann, and T. Gross. An evaluation of inter-vehicle ad hoc networks based on realistic vehicular traces ...

مرکز منطقه ای اطلاع رساني علوم و فناوري - Generation of ...

Computational experiments demonstrate that using basic evolutionary heuristics for optimising VehILux parameters on a given problem instance permits to improve the model realism. However, in some cases, the results significantly deviate from real traffic count data. This is due to the route generation method of the VehILux model, which does not take into account specific behaviour of drivers ...

CiteSeerX — An Ant-Based Model for Multiple Sequence Alignment

CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): Abstract. Multiple sequence alignment is a key process in today’s biology, and finding a relevant alignment of several sequences is much more challenging than just optimizing some improbable evaluation functions. Our approach for addressing multiple sequence alignment focuses on the building of structures in a new ...

An Ant-Based Model for Multiple Sequence ... - CiteSeerX

CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): www.litislab.eu Abstract. Multiple sequence alignment is a key process in today’s biology, and finding a relevant alignment of several sequences is much more challenging than just optimizing some improbable evaluation functions. Our approach for addressing multiple sequence alignment focuses on the building of ...

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Subventions de l'État aux associations Ce site vous permettra de consulter de façon détaillée les subventions faites aux associations entre 2010 et 2018 (publié dans les PLF Jaunes entre 2012 et 2020).

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Biographie de Christian Fournier, photographe professionnel freelance à Paris, dans son studio ou en extérieur dans le monde entier, il excelle en mode, publicité, industrie, reportage, art, sous-marin, événementiel, corporate, presse, mariage

Robert G. Reynolds Cultural Algorithms


A thorough look at how societies can use cultural algorithms to understand human social evolution For those working in computational intelligence, developing an understanding of how cultural algorithms and social intelligence form the essential framework for the evolution of human social interaction is essential. This book, Cultural Algorithms: Tools to Model Complex Dynamic Social Systems , is the foundation of that study. It showcases how we can use cultural algorithms to organize social structures and develop socio-political systems that work. For such a vast topic, the text covers everything from the history of the development of cultural algorithms and the basic framework with which it was organized. Readers will also learn how other nature-inspired algorithms can be expressed and how to use social metrics to assess the performance of various algorithms.  In addition to these topics, the book covers topics including: ● The CAT system including the Repast Simphony System and CAT Sample Runs ● How to problem solve using social networks in cultural algorithms with auctions ● Understanding Common Value Action to enhance Social Knowledge Distribution Systems ● Case studies on team formations ● An exploration of virtual worlds using cultural algorithms For industry professionals or new students, Cultural Algorithms provides an impactful and thorough look at both social intelligence and how human social evolution translates into the modern world.

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Pawel Cichosz Data Mining Algorithms


Data Mining Algorithms is a practical, technically-oriented guide to data mining algorithms that covers the most important algorithms for building classification, regression, and clustering models, as well as techniques used for attribute selection and transformation, model quality evaluation, and creating model ensembles. The author presents many of the important topics and methodologies widely used in data mining, whilst demonstrating the internal operation and usage of data mining algorithms using examples in R.

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Группа авторов The Handbook of Evolutionary Psychology


The foundations of practice and the most recent discoveries in theintriguing newfield of evolutionary psychology Why is the mind designed the way it is? How does input from the environment interact with the mind to produce behavior? By taking aim at such questions, the science of evolutionary psychology has emerged as a vibrant new discipline producing groundbreaking insights. In The Handbook of Evolutionary Psychology, leading contributors discuss the foundations of the field as well as recent discoveries currently shaping this burgeoning area of psychology. Guided by an editorial board made up of such luminaries as Leda Cosmides, John Tooby, Don Symons, Steve Pinker, Martin Daly, Margo Wilson, and Helena Cronin, the text's chapters delve into a comprehensive range of topics, covering the full range of the discipline: Foundations of evolutionary psychology Survival Mating Parenting and kinship Group living Interfaces with traditional disciplines of evolutionary psychology And interfaces across disciplines. In addition to an in-depth survey of the theory and practice of evolutionary psychology, the text also features an enlightening discussion of this discipline in the context of the law, medicine, and culture. An Afterword by Richard Dawkins provides some final thoughts from the renowned writer and exponent of evolutionary theory. Designed to set the standard for handbooks in the field, The Handbook of Evolutionary Psychology is an indispensable reference tool for every evolutionary psychologist and student.

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Juan Li Decomposition-based Evolutionary Optimization in Complex Environments


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