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Nature-Inspired Algorithms and Applied Optimization, Xin-She Yang


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Автор: Xin-She Yang
Название:  Nature-Inspired Algorithms and Applied Optimization
ISBN: 9783319884653
Издательство: Springer
Классификация:




ISBN-10: 3319884654
Обложка/Формат: Soft cover
Страницы: 330
Вес: 0.53 кг.
Дата издания: 2018
Серия: Studies in Computational Intelligence
Язык: English
Издание: Softcover reprint of
Иллюстрации: 100 tables, color; 28 illustrations, color; 14 illustrations, black and white; xi, 330 p. 42 illus., 28 illus. in color.
Размер: Book (Paperback Initiative)
Читательская аудитория: Professional & vocational
Основная тема: Engineering
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: 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.
Дополнительное описание: Mathematical Analysis of Nature-Inspired Algorithms.- A Review of No Free Lunch Theorems, and their Implications for Metaheuristic Optimisation.- Global Convergence Analysis of Cuckoo Search Using Markov Theory.- On Effeciently Solving the Vehicle Routing



Nature-Inspired Algorithms and Applied Optimization

Автор: Xin-She Yang
Название: Nature-Inspired Algorithms and Applied Optimization
ISBN: 3319676687 ISBN-13(EAN): 9783319676685
Издательство: Springer
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Цена: 20962.00 р.
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Описание: Mathematical Analysis of Nature-Inspired Algorithms.- A Review of No Free Lunch Theorems, and their Implications for Metaheuristic Optimisation.- Global Convergence Analysis of Cuckoo Search Using Markov Theory.- On Effeciently Solving the Vehicle Routing Problem with Time Windows Using the Bat Algorithm.- Variants of the Flower Pollination Algorithm: A Review.

Nature-Inspired Optimization Algorithms

Автор: Yang Xin She
Название: Nature-Inspired Optimization Algorithms
ISBN: 0128100605 ISBN-13(EAN): 9780128100608
Издательство: Elsevier Science
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Цена: 12462.00 р.
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Описание: 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.

Ensembles of Type 2 Fuzzy Neural Models and Their Optimization with Bio-Inspired Algorithms for Time Series Prediction

Автор: Soto Jesus, Melin Patricia, Castillo Oscar
Название: Ensembles of Type 2 Fuzzy Neural Models and Their Optimization with Bio-Inspired Algorithms for Time Series Prediction
ISBN: 3319712632 ISBN-13(EAN): 9783319712635
Издательство: Springer
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Цена: 6986.00 р.
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Описание: This book focuses on the fields of hybrid intelligent systems based on fuzzy systems, neural networks, bio-inspired algorithms and time series. Prediction errors are evaluated by the following metrics: Mean Absolute Error, Mean Square Error, Root Mean Square Error, Mean Percentage Error and Mean Absolute Percentage Error.

Inverse Problems: Tikhonov Theory and Algorithms

Автор: Ito Kazufumi, Jin Bangti
Название: Inverse Problems: Tikhonov Theory and Algorithms
ISBN: 9814596191 ISBN-13(EAN): 9789814596190
Издательство: World Scientific Publishing
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Цена: 17741.00 р.
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Описание:

Inverse problems arise in practical applications whenever one needs to deduce unknowns from observables. This monograph is a valuable contribution to the highly topical field of computational inverse problems. Both mathematical theory and numerical algorithms for model-based inverse problems are discussed in detail. The mathematical theory focuses on nonsmooth Tikhonov regularization for linear and nonlinear inverse problems. The computational methods include nonsmooth optimization algorithms, direct inversion methods and uncertainty quantification via Bayesian inference.

The book offers a comprehensive treatment of modern techniques, and seamlessly blends regularization theory with computational methods, which is essential for developing accurate and efficient inversion algorithms for many practical inverse problems.

It demonstrates many current developments in the field of computational inversion, such as value function calculus, augmented Tikhonov regularization, multi-parameter Tikhonov regularization, semismooth Newton method, direct sampling method, uncertainty quantification and approximate Bayesian inference. It is written for graduate students and researchers in mathematics, natural science and engineering.

Topological Optimization and Optimal Transport: In the Applied Sciences

Автор: Maitine Bergounioux, ?douard Oudet, Martin Rumpf,
Название: Topological Optimization and Optimal Transport: In the Applied Sciences
ISBN: 3110439263 ISBN-13(EAN): 9783110439267
Издательство: Walter de Gruyter
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Цена: 26024.00 р.
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Описание:

By discussing topics such as shape representations, relaxation theory and optimal transport, trends and synergies of mathematical tools required for optimization of geometry and topology of shapes are explored. Furthermore, applications in science and engineering, including economics, social sciences, biology, physics and image processing are covered.

Contents
Part I

  • Geometric issues in PDE problems related to the infinity Laplace operator
  • Solution of free boundary problems in the presence of geometric uncertainties
  • Distributed and boundary control problems for the semidiscrete Cahn-Hilliard/Navier-Stokes system with nonsmooth Ginzburg-Landau energies
  • High-order topological expansions for Helmholtz problems in 2D
  • On a new phase field model for the approximation of interfacial energies of multiphase systems
  • Optimization of eigenvalues and eigenmodes by using the adjoint method
  • Discrete varifolds and surface approximation

Part II

  • Weak Monge-Ampere solutions of the semi-discrete optimal transportation problem
  • Optimal transportation theory with repulsive costs
  • Wardrop equilibria: long-term variant, degenerate anisotropic PDEs and numerical approximations
  • On the Lagrangian branched transport model and the equivalence with its Eulerian formulation
  • On some nonlinear evolution systems which are perturbations of Wasserstein gradient flows
  • Pressureless Euler equations with maximal density constraint: a time-splitting scheme
  • Convergence of a fully discrete variational scheme for a thin-film equatio
  • Interpretation of finite volume discretization schemes for the Fokker-Planck equation as gradient flows for the discrete Wasserstein distance
Handbook of research on soft computing and nature-inspired algorithms

Автор: SHANDILYA, SHANDILYA, DEEP & NAG
Название: Handbook of research on soft computing and nature-inspired algorithms
ISBN: 1522521283 ISBN-13(EAN): 9781522521280
Издательство: Turpin
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Цена: 41395.00 р.
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Описание: Soft computing and nature-inspired computing both play a significant role in developing a better understanding to machine learning. When studied together, they can offer new perspectives on the learning process of machines. The Handbook of Research on Soft Computing and Nature-Inspired Algorithms is an essential source for the latest scholarly research on applications of nature-inspired computing and soft computational systems. Featuring comprehensive coverage on a range of topics and perspectives such as swarm intelligence, speech recognition, and electromagnetic problem solving, this publication is ideally designed for students, researchers, scholars, professionals, and practitioners seeking current research on the advanced workings of intelligence in computing systems.

Advanced Optimization by Nature-Inspired Algorithms

Автор: Omid Bozorg-Haddad
Название: Advanced Optimization by Nature-Inspired Algorithms
ISBN: 9811052204 ISBN-13(EAN): 9789811052200
Издательство: Springer
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Цена: 18167.00 р.
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Описание: This book, compiles, presents, and explains the most important meta-heuristic and evolutionary optimization algorithms whose successful performance has been proven in different fields of engineering, and it includes application of these algorithms to important engineering optimization problems. In addition, this book guides readers to studies that have implemented these algorithms by providing a literature review on developments and applications of each algorithm. This book is intended for students, but can be used by researchers and professionals in the area of engineering optimization.

Advanced Optimization by Nature-Inspired Algorithms

Автор: Omid Bozorg-Haddad
Название: Advanced Optimization by Nature-Inspired Algorithms
ISBN: 981135345X ISBN-13(EAN): 9789811353451
Издательство: Springer
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Цена: 12577.00 р.
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Описание: This book, compiles, presents, and explains the most important meta-heuristic and evolutionary optimization algorithms whose successful performance has been proven in different fields of engineering, and it includes application of these algorithms to important engineering optimization problems. In addition, this book guides readers to studies that have implemented these algorithms by providing a literature review on developments and applications of each algorithm. This book is intended for students, but can be used by researchers and professionals in the area of engineering optimization.

Introduction to nature-inspired optimization

Автор: Lindfield, George (professor, School Of Engineering And Applied Science, Aston University) Penny, John (professor, School Of Engineering And Applied S
Название: Introduction to nature-inspired optimization
ISBN: 0128036362 ISBN-13(EAN): 9780128036365
Издательство: Elsevier Science
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Цена: 15993.00 р.
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Описание:

Introduction to Nature-Inspired Optimization brings together many of the innovative mathematical methods for non-linear optimization that have their origins in the way various species behave in order to optimize their chances of survival. The book describes each method, examines their strengths and weaknesses, and where appropriate, provides the MATLAB code to give practical insight into the detailed structure of these methods and how they work.

Nature-inspired algorithms emulate processes that are found in the natural world, spurring interest for optimization. Lindfield/Penny provide concise coverage to all the major algorithms, including genetic algorithms, artificial bee colony algorithms, ant colony optimization and the cuckoo search algorithm, among others. This book provides a quick reference to practicing engineers, researchers and graduate students who work in the field of optimization.

Modern Music-Inspired Optimization Algorithms for Electric Power Systems

Автор: Mohammad Kiani-Moghaddam; Mojtaba Shivaie; Philip
Название: Modern Music-Inspired Optimization Algorithms for Electric Power Systems
ISBN: 3030120430 ISBN-13(EAN): 9783030120436
Издательство: Springer
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Цена: 27950.00 р.
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Описание:

In today’s world, with an increase in the breadth and scope of real-world engineering optimization problems as well as with the advent of big data, improving the performance and efficiency of algorithms for solving such problems has become an indispensable need for specialists and researchers. In contrast to conventional books in the field that employ traditional single-stage computational, single-dimensional, and single-homogeneous optimization algorithms, this book addresses multiple newfound architectures for meta-heuristic music-inspired optimization algorithms. These proposed algorithms, with multi-stage computational, multi-dimensional, and multi-inhomogeneous structures, bring about a new direction in the architecture of meta-heuristic algorithms for solving complicated, real-world, large-scale, non-convex, non-smooth engineering optimization problems having a non-linear, mixed-integer nature with big data. The architectures of these new algorithms may also be appropriate for finding an optimal solution or a Pareto-optimal solution set with higher accuracy and speed in comparison to other optimization algorithms, when feasible regions of the solution space and/or dimensions of the optimization problem increase.
This book, unlike conventional books on power systems problems that only consider simple and impractical models, deals with complicated, techno-economic, real-world, large-scale models of power systems operation and planning. Innovative applicable ideas in these models make this book a precious resource for specialists and researchers with a background in power systems operation and planning.
Provides an understanding of the optimization problems and algorithms, particularly meta-heuristic optimization algorithms, found in fields such as engineering, economics, management, and operations research;Enhances existing architectures and develops innovative architectures for meta-heuristic music-inspired optimization algorithms in order to deal with complicated, real-world, large-scale, non-convex, non-smooth engineering optimization problems having a non-linear, mixed-integer nature with big data;Addresses innovative multi-level, techno-economic, real-world, large-scale, computational-logical frameworks for power systems operation and planning, and illustrates practical training on implementation of the frameworks using the meta-heuristic music-inspired optimization algorithms.
Optimization using evolutionary algorithms and metaheuristics

Автор: Kaushik Kumar and J. Paulo Davim
Название: Optimization using evolutionary algorithms and metaheuristics
ISBN: 0367260441 ISBN-13(EAN): 9780367260446
Издательство: Taylor&Francis
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Цена: 25265.00 р.
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Описание: This book covers developments and advances of algorithm based optimization techniques These techniques were only used for non-engineering problems. This book applies them to engineering problems.

Applied Nature-Inspired Computing: Algorithms and Case Studies

Автор: Dey Nilanjan, Ashour Amira S., Bhattacharyya Siddhartha
Название: Applied Nature-Inspired Computing: Algorithms and Case Studies
ISBN: 9811392625 ISBN-13(EAN): 9789811392627
Издательство: Springer
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Цена: 13974.00 р.
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Описание: This book presents a cutting-edge research procedure in the Nature-Inspired Computing (NIC) domain and its connections with computational intelligence areas in real-world engineering applications. It introduces readers to a broad range of algorithms, such as genetic algorithms, particle swarm optimization, the firefly algorithm, flower pollination algorithm, collision-based optimization algorithm, bat algorithm, ant colony optimization, and multi-agent systems. In turn, it provides an overview of meta-heuristic algorithms, comparing the advantages and disadvantages of each. Moreover, the book provides a brief outline of the integration of nature-inspired computing techniques and various computational intelligence paradigms, and highlights nature-inspired computing techniques in a range of applications, including: evolutionary robotics, sports training planning, assessment of water distribution systems, flood simulation and forecasting, traffic control, gene expression analysis, antenna array design, and scheduling/dynamic resource management.


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