Nature-Inspired Algorithms for Optimisation

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Publisher : Springer Science & Business Media
ISBN 13 : 3642002668
Total Pages : 524 pages
Book Rating : 4.6/5 (42 download)

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Book Synopsis Nature-Inspired Algorithms for Optimisation by : Raymond Chiong

Download or read book Nature-Inspired Algorithms for Optimisation written by Raymond Chiong and published by Springer Science & Business Media. This book was released on 2009-04-28 with total page 524 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nature-Inspired Algorithms have been gaining much popularity in recent years due to the fact that many real-world optimisation problems have become increasingly large, complex and dynamic. The size and complexity of the problems nowadays require the development of methods and solutions whose efficiency is measured by their ability to find acceptable results within a reasonable amount of time, rather than an ability to guarantee the optimal solution. This volume 'Nature-Inspired Algorithms for Optimisation' is a collection of the latest state-of-the-art algorithms and important studies for tackling various kinds of optimisation problems. It comprises 18 chapters, including two introductory chapters which address the fundamental issues that have made optimisation problems difficult to solve and explain the rationale for seeking inspiration from nature. The contributions stand out through their novelty and clarity of the algorithmic descriptions and analyses, and lead the way to interesting and varied new applications.

Hybrid Metaheuristics

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Publisher : Springer
ISBN 13 : 3642306713
Total Pages : 464 pages
Book Rating : 4.6/5 (423 download)

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Book Synopsis Hybrid Metaheuristics by : El-ghazali Talbi

Download or read book Hybrid Metaheuristics written by El-ghazali Talbi and published by Springer. This book was released on 2012-07-31 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt: The main goal of this book is to provide a state of the art of hybrid metaheuristics. The book provides a complete background that enables readers to design and implement hybrid metaheuristics to solve complex optimization problems (continuous/discrete, mono-objective/multi-objective, optimization under uncertainty) in a diverse range of application domains. Readers learn to solve large scale problems quickly and efficiently combining metaheuristics with complementary metaheuristics, mathematical programming, constraint programming and machine learning. Numerous real-world examples of problems and solutions demonstrate how hybrid metaheuristics are applied in such fields as networks, logistics and transportation, bio-medical, engineering design, scheduling.

Transactions on Computational Science XXI

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Publisher : Springer
ISBN 13 : 364245318X
Total Pages : 380 pages
Book Rating : 4.6/5 (424 download)

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Book Synopsis Transactions on Computational Science XXI by : Marina L. Gavrilova

Download or read book Transactions on Computational Science XXI written by Marina L. Gavrilova and published by Springer. This book was released on 2013-11-25 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: This, the 21st issue of the Transactions on Computational Science journal, edited by Ajith Abraham, is devoted to the topic of nature-inspired computing and applications. The 15 full papers included in the volume focus on the topics of neurocomputing, evolutionary algorithms, swarm intelligence, artificial immune systems, membrane computing, computing with words, artificial life and hybrid approaches.

Nature-Inspired Optimization Algorithms

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Author :
Publisher : Elsevier
ISBN 13 : 0124167454
Total Pages : 277 pages
Book Rating : 4.1/5 (241 download)

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Book Synopsis Nature-Inspired Optimization Algorithms by : Xin-She Yang

Download or read book Nature-Inspired Optimization Algorithms written by Xin-She Yang and published by Elsevier. This book was released on 2014-02-17 with total page 277 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nature-Inspired Optimization Algorithms provides a systematic introduction to all major nature-inspired algorithms for optimization. The book's unified approach, balancing algorithm introduction, theoretical background and practical implementation, complements extensive literature with well-chosen case studies to illustrate how these algorithms work. Topics include particle swarm optimization, ant and bee algorithms, simulated annealing, cuckoo search, firefly algorithm, bat algorithm, flower algorithm, harmony search, algorithm analysis, constraint handling, hybrid methods, parameter tuning and control, as well as multi-objective optimization. This book can serve as an introductory book for graduates, doctoral students and lecturers in computer science, engineering and natural sciences. It can also serve a source of inspiration for new applications. Researchers and engineers as well as experienced experts will also find it a handy reference. - Discusses and summarizes the latest developments in nature-inspired algorithms with comprehensive, timely literature - Provides a theoretical understanding as well as practical implementation hints - Provides a step-by-step introduction to each algorithm

Handbook of Research on Nature-Inspired Computing for Economics and Management

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Author :
Publisher : IGI Global
ISBN 13 : 1591409853
Total Pages : 1066 pages
Book Rating : 4.5/5 (914 download)

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Book Synopsis Handbook of Research on Nature-Inspired Computing for Economics and Management by : Rennard, Jean-Philippe

Download or read book Handbook of Research on Nature-Inspired Computing for Economics and Management written by Rennard, Jean-Philippe and published by IGI Global. This book was released on 2006-09-30 with total page 1066 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book provides applications of nature inspired computing for economic theory and practice, finance and stock-market, manufacturing systems, marketing, e-commerce, e-auctions, multi-agent systems and bottom-up simulations for social sciences and operations management"--Provided by publisher.

Multi-Objective Optimization using Artificial Intelligence Techniques

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Publisher : Springer
ISBN 13 : 3030248356
Total Pages : 66 pages
Book Rating : 4.0/5 (32 download)

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Book Synopsis Multi-Objective Optimization using Artificial Intelligence Techniques by : Seyedali Mirjalili

Download or read book Multi-Objective Optimization using Artificial Intelligence Techniques written by Seyedali Mirjalili and published by Springer. This book was released on 2019-07-24 with total page 66 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the most well-regarded and recent nature-inspired algorithms capable of solving optimization problems with multiple objectives. Firstly, it provides preliminaries and essential definitions in multi-objective problems and different paradigms to solve them. It then presents an in-depth explanations of the theory, literature review, and applications of several widely-used algorithms, such as Multi-objective Particle Swarm Optimizer, Multi-Objective Genetic Algorithm and Multi-objective GreyWolf Optimizer Due to the simplicity of the techniques and flexibility, readers from any field of study can employ them for solving multi-objective optimization problem. The book provides the source codes for all the proposed algorithms on a dedicated webpage.

Evolutionary Multi-Agent Systems

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Publisher : Springer
ISBN 13 : 3319513885
Total Pages : 216 pages
Book Rating : 4.3/5 (195 download)

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Book Synopsis Evolutionary Multi-Agent Systems by : Aleksander Byrski

Download or read book Evolutionary Multi-Agent Systems written by Aleksander Byrski and published by Springer. This book was released on 2016-12-21 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book addresses agent-based computing, concentrating in particular on evolutionary multi-agent systems (EMAS), which have been developed since 1996 at the AGH University of Science and Technology in Cracow, Poland. It provides the relevant background information on and a detailed description of this computing paradigm, along with key experimental results. Readers will benefit from the insightful discussion, which primarily concerns the efficient implementation of computing frameworks for developing EMAS and similar computing systems, as well as a detailed formal model. Theoretical deliberations demonstrating that computing with EMAS always helps to find the optimal solution are also included, rounding out the coverage.

Nature-Inspired Algorithms for Big Data Frameworks

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Publisher : IGI Global
ISBN 13 : 1522558535
Total Pages : 435 pages
Book Rating : 4.5/5 (225 download)

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Book Synopsis Nature-Inspired Algorithms for Big Data Frameworks by : Banati, Hema

Download or read book Nature-Inspired Algorithms for Big Data Frameworks written by Banati, Hema and published by IGI Global. This book was released on 2018-09-28 with total page 435 pages. Available in PDF, EPUB and Kindle. Book excerpt: As technology continues to become more sophisticated, mimicking natural processes and phenomena becomes more of a reality. Continued research in the field of natural computing enables an understanding of the world around us, in addition to opportunities for manmade computing to mirror the natural processes and systems that have existed for centuries. Nature-Inspired Algorithms for Big Data Frameworks is a collection of innovative research on the methods and applications of extracting meaningful information from data using algorithms that are capable of handling the constraints of processing time, memory usage, and the dynamic and unstructured nature of data. Highlighting a range of topics including genetic algorithms, data classification, and wireless sensor networks, this book is ideally designed for computer engineers, software developers, IT professionals, academicians, researchers, and upper-level students seeking current research on the application of nature and biologically inspired algorithms for handling challenges posed by big data in diverse environments.

Evolutionary Algorithms for Solving Multi-Objective Problems

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Publisher : Springer Science & Business Media
ISBN 13 : 0387367977
Total Pages : 810 pages
Book Rating : 4.3/5 (873 download)

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Book Synopsis Evolutionary Algorithms for Solving Multi-Objective Problems by : Carlos Coello Coello

Download or read book Evolutionary Algorithms for Solving Multi-Objective Problems written by Carlos Coello Coello and published by Springer Science & Business Media. This book was released on 2007-08-26 with total page 810 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook is a second edition of Evolutionary Algorithms for Solving Multi-Objective Problems, significantly expanded and adapted for the classroom. The various features of multi-objective evolutionary algorithms are presented here in an innovative and student-friendly fashion, incorporating state-of-the-art research. The book disseminates the application of evolutionary algorithm techniques to a variety of practical problems. It contains exhaustive appendices, index and bibliography and links to a complete set of teaching tutorials, exercises and solutions.

Biologically-Inspired Optimisation Methods

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Publisher : Springer
ISBN 13 : 3642012620
Total Pages : 365 pages
Book Rating : 4.6/5 (42 download)

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Book Synopsis Biologically-Inspired Optimisation Methods by : Andrew Lewis

Download or read book Biologically-Inspired Optimisation Methods written by Andrew Lewis and published by Springer. This book was released on 2009-05-12 with total page 365 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers the latest theories, applications and techniques in Biologically-Inspired Optimisation Methods. Many chapters derive from studies presented at workshops and international conferences on e-Science, Grid Computing and Evolutionary computation.

Handbook of Research on Advancements of Swarm Intelligence Algorithms for Solving Real-World Problems

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Publisher : IGI Global
ISBN 13 : 1799832244
Total Pages : 482 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Handbook of Research on Advancements of Swarm Intelligence Algorithms for Solving Real-World Problems by : Cheng, Shi

Download or read book Handbook of Research on Advancements of Swarm Intelligence Algorithms for Solving Real-World Problems written by Cheng, Shi and published by IGI Global. This book was released on 2020-04-24 with total page 482 pages. Available in PDF, EPUB and Kindle. Book excerpt: The use of optimization algorithms has seen an emergence in various professional fields due to its ability to process data and information in an efficient and productive manner. Combining computational intelligence with these algorithms has created a trending subject of research on how much more beneficial intelligent-inspired algorithms can be within companies and organizations. As modern theories and applications are continually being developed in this area, professionals are in need of current research on how intelligent algorithms are advancing in the real world. TheHandbook of Research on Advancements of Swarm Intelligence Algorithms for Solving Real-World Problems is a pivotal reference source that provides vital research on the development of swarm intelligence algorithms and their implementation into current issues. While highlighting topics such as multi-agent systems, bio-inspired computing, and evolutionary programming, this publication explores various concepts and theories of swarm intelligence and outlines future directions of development. This book is ideally designed for IT specialists, researchers, academicians, engineers, developers, practitioners, and students seeking current research on the real-world applications of intelligent algorithms.

Intelligence Science I

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Publisher : Springer
ISBN 13 : 3319681214
Total Pages : 470 pages
Book Rating : 4.3/5 (196 download)

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Book Synopsis Intelligence Science I by : Zhongzhi Shi

Download or read book Intelligence Science I written by Zhongzhi Shi and published by Springer. This book was released on 2017-10-16 with total page 470 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Second International Conference on Intelligence Science, ICIS 2017, held in Shanghai, China, in October 2017. The 38 full papers and 9 short papers presented were carefully reviewed and selected from 82 submissions. They deal with key issues in intelligence science and have been organized in the following topical sections: theory of intelligence science; cognitive computing; big data analysis and machine learning; machine perception; intelligent information processing; and intelligent applications.

Nature-Inspired Algorithms and Applied Optimization

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Publisher : Springer
ISBN 13 : 9783319884653
Total Pages : 0 pages
Book Rating : 4.8/5 (846 download)

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Book Synopsis Nature-Inspired Algorithms and Applied Optimization by : Xin-She Yang

Download or read book Nature-Inspired Algorithms and Applied Optimization written by Xin-She Yang and published by Springer. This book was released on 2018-08-15 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reviews the state-of-the-art developments in nature-inspired algorithms and their applications in various disciplines, ranging from feature selection and engineering design optimization to scheduling and vehicle routing. It introduces each algorithm and its implementation with case studies as well as extensive literature reviews, and also includes self-contained chapters featuring theoretical analyses, such as convergence analysis and no-free-lunch theorems so as to provide insights into the current nature-inspired optimization algorithms. Topics include ant colony optimization, the bat algorithm, B-spline curve fitting, cuckoo search, feature selection, economic load dispatch, the firefly algorithm, the flower pollination algorithm, knapsack problem, octonian and quaternion representations, particle swarm optimization, scheduling, wireless networks, vehicle routing with time windows, and maximally different alternatives. This timely book serves as a practical guide and reference resource for students, researchers and professionals.

Nature-Inspired Informatics for Intelligent Applications and Knowledge Discovery: Implications in Business, Science, and Engineering

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Publisher : IGI Global
ISBN 13 : 1605667064
Total Pages : 449 pages
Book Rating : 4.6/5 (56 download)

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Book Synopsis Nature-Inspired Informatics for Intelligent Applications and Knowledge Discovery: Implications in Business, Science, and Engineering by : Chiong, Raymond

Download or read book Nature-Inspired Informatics for Intelligent Applications and Knowledge Discovery: Implications in Business, Science, and Engineering written by Chiong, Raymond and published by IGI Global. This book was released on 2009-07-31 with total page 449 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recently, nature has stimulated many successful techniques, algorithms, and computational applications allowing conventionally difficult problems to be solved through novel computing systems. Nature-Inspired Informatics for Intelligent Applications and Knowledge Discovery: Implications in Business, Science, and Engineering provides the latest findings in nature-inspired algorithms and their applications for breakthroughs in a wide range of disciplinary fields. This defining reference collection contains chapters written by leading researchers and well-known academicians within the field, offering readers a valuable and enriched accumulation of knowledge.

Intelligent Data Analytics for Power and Energy Systems

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Publisher : Springer Nature
ISBN 13 : 9811660816
Total Pages : 649 pages
Book Rating : 4.8/5 (116 download)

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Book Synopsis Intelligent Data Analytics for Power and Energy Systems by : Hasmat Malik

Download or read book Intelligent Data Analytics for Power and Energy Systems written by Hasmat Malik and published by Springer Nature. This book was released on 2022-02-17 with total page 649 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book brings together state-of-the-art advances in intelligent data analytics as driver of the future evolution of PaE systems. In the modern power and energy (PaE) domain, the increasing penetration of renewable energy sources (RES) and the consequent empowerment of consumers as a central and active solution to deal with the generation and development variability are driving the PaE system towards a historic paradigm shift. The small-scale, diversity, and especially the number of new players involved in the PaE system potentiate a significant growth of generated data. Moreover, advances in communication (between IoT devices and M2M: machine to machine, man to machine, etc.) and digitalization hugely increased the volume of data that results from PaE components, installations, and systems operation. This data is becoming more and more important for PaE systems operation, maintenance, planning, and scheduling with relevant impact on all involved entities, from producers, consumer,s and aggregators to market and system operators. However, although the PaE community is fully aware of the intrinsic value of those data, the methods to deal with it still necessitate substantial enhancements, development and research. Intelligent data analytics is thereby playing a fundamental role in this domain, by enabling stakeholders to expand their decision-making method and achieve the awareness on the PaE environment. The editors also included demonstrated codes for presented problems for better understanding for beginners.

Natural Risk Management and Engineering

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Publisher : Springer Nature
ISBN 13 : 3030393917
Total Pages : 243 pages
Book Rating : 4.0/5 (33 download)

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Book Synopsis Natural Risk Management and Engineering by : Milan Gocić

Download or read book Natural Risk Management and Engineering written by Milan Gocić and published by Springer Nature. This book was released on 2020-03-12 with total page 243 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book summarizes the research being pursued as part of the Erasmus+ CBHE KA2 project entitled "Development of master curricula for natural disasters risk management in Western Balkan countries” (NatRisk), which aims to educate experts on the prevention and management of natural disasters in the Western Balkan region in line with national and EU policies. The project has successfully developed and implemented master curricula and educational training in the field of natural disasters risk management, and a methodology for the identification and prevention of natural disasters. Consisting of 11 chapters, the book analyzes and discusses topics such as risk assessment tools and quality methods, the different approaches for civil-military collaboration, natural disasters risk management in Bosnia and Herzegovina, leadership models for managing crises resulting from natural disasters, natural disasters in industrial areas, natural risk management in geotechnics, flood risk modeling, adaptive neuro-fuzzy inference models for flood prediction, collapse prediction of masonry arches, an algorithm for fire truck dispatch in emergency situations, and processing drought data in a GIS environment.

Deep Learning Techniques and Optimization Strategies in Big Data Analytics

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Author :
Publisher : IGI Global
ISBN 13 : 1799811948
Total Pages : 355 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Deep Learning Techniques and Optimization Strategies in Big Data Analytics by : Thomas, J. Joshua

Download or read book Deep Learning Techniques and Optimization Strategies in Big Data Analytics written by Thomas, J. Joshua and published by IGI Global. This book was released on 2019-11-29 with total page 355 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many approaches have sprouted from artificial intelligence (AI) and produced major breakthroughs in the computer science and engineering industries. Deep learning is a method that is transforming the world of data and analytics. Optimization of this new approach is still unclear, however, and there’s a need for research on the various applications and techniques of deep learning in the field of computing. Deep Learning Techniques and Optimization Strategies in Big Data Analytics is a collection of innovative research on the methods and applications of deep learning strategies in the fields of computer science and information systems. While highlighting topics including data integration, computational modeling, and scheduling systems, this book is ideally designed for engineers, IT specialists, data analysts, data scientists, engineers, researchers, academicians, and students seeking current research on deep learning methods and its application in the digital industry.