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Mathematical Foundations of Nature-Inspired Algorithms, Xin-She Yang; Xing-Shi He


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Автор: Xin-She Yang; Xing-Shi He
Название:  Mathematical Foundations of Nature-Inspired Algorithms
ISBN: 9783030169350
Издательство: Springer
Классификация:






ISBN-10: 3030169359
Обложка/Формат: Soft cover
Страницы: 107
Вес: 0.20 кг.
Дата издания: 2019
Серия: SpringerBriefs in Optimization
Язык: English
Издание: 1st ed. 2019
Иллюстрации: 2 tables, color; 2 illustrations, color; 2 illustrations, black and white; xi, 107 p. 4 illus., 2 illus. in color.
Размер: 234 x 156 x 6
Читательская аудитория: Professional & vocational
Основная тема: Mathematics
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: This book presents a systematic approach to analyze nature-inspired algorithms. Beginning with an introduction to optimization methods and algorithms, this book moves on to provide a unified framework of mathematical analysis for convergence and stability. Specific nature-inspired algorithms include: swarm intelligence, ant colony optimization, particle swarm optimization, bee-inspired algorithms, bat algorithm, firefly algorithm, and cuckoo search. Algorithms are analyzed from a wide spectrum of theories and frameworks to offer insight to the main characteristics of algorithms and understand how and why they work for solving optimization problems. In-depth mathematical analyses are carried out for different perspectives, including complexity theory, fixed point theory, dynamical systems, self-organization, Bayesian framework, Markov chain framework, filter theory, statistical learning, and statistical measures. Students and researchers in optimization, operations research, artificial intelligence, data mining, machine learning, computer science, and management sciences will see the pros and cons of a variety of algorithms through detailed examples and a comparison of algorithms.
Дополнительное описание: 1 Introduction to Optimization.- 2 Nature-Inspired Algorithms.- 3 Mathematical Foundations.- 4 Mathematical Analysis I.- 5 Mathematical Analysis II.



Mathematical Physics: A Modern Introduction To Its Foundations

Автор: Sadri Hassani
Название: Mathematical Physics: A Modern Introduction To Its Foundations
ISBN: 3319011944 ISBN-13(EAN): 9783319011943
Издательство: Springer
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Цена: 11179.00 р.
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Описание:

This book is for physics students interested in the mathematics they use and for mathematics students interested in seeing how some of the ideas of their discipline find realization in an applied setting. The presentation tries to strike a balance between formalism and application, between abstract and concrete. The interconnections among the various topics are clarified both by the use of vector spaces as a central unifying theme, recurring throughout the book, and by putting ideas into their historical context. Enough of the essential formalism is included to make the presentation self-contained.

The book is divided into eight parts: The first covers finite- dimensional vector spaces and the linear operators defined on them. The second is devoted to infinite-dimensional vector spaces, and includes discussions of the classical orthogonal polynomials and of Fourier series and transforms. The third part deals with complex analysis, including complex series and their convergence, the calculus of residues, multivalued functions, and analytic continuation. Part IV treats ordinary differential equations, concentrating on second-order equations and discussing both analytical and numerical methods of solution. The next part deals with operator theory, focusing on integral and Sturm--Liouville operators. Part VI is devoted to Green's functions, both for ordinary differential equations and in multidimensional spaces. Parts VII and VIII contain a thorough discussion of differential geometry and Lie groups and their applications, concluding with Noether's theorem on the relationship between symmetries and conservation laws.

Intended for advanced undergraduates or beginning graduate students, this comprehensive guide should also prove useful as a refresher or reference for physicists and applied mathematicians. Over 300 worked-out examples and more than 800 problems provide valuable learning aids.

Numerous enhancements and revision are incorporated into this new edition. For example, fiber bundle techniques are used to introduce differential geometry. This more elegant and intuitive approach naturally connects differential geometry with not only the general theory of relativity, but also gauge theories of fundamental forces.

Some praise for the previous edition:

PAGEOPH Pure and Applied Geophysics]

Review by Daniel Wojcik, University of Maryland

"This volume should be a welcome addition to any collection. The book is well written and explanations are usually clear. Lives of famous mathematicians and physicists are scattered within the book. They are quite extended, often amusing, making nice interludes. Numerous exercises help the student practice the methods introduced. ... I have recently been using this book for an extended time and acquired a liking for it. Among all the available books treating mathematical methods of physics this one certainly stands out and assuredly it would suit the needs of many physics readers."

ZENTRALBLATT MATH

Review by G.Roepstorff, University of Aachen, Germany

..". Unlike most existing texts with the same emphasis and audience, which are merely collections of facts and formulas, the present book is more systematic, self-contained, with a level of presentation that tends to be more formal and abstract. This entails proving a large number of theorems, lemmas, and corollaries, deferring most of the applications that physics students might be interested in to the example sections in small print. Indeed, there are 350 worked-out examples and about 850 problems. ... A very nice feature is the way the author intertwines the formalism with the life stories and anecdotes of some mathematicians and physicists, leading at their times. As is often the case, the historical view point helps to understand and appreciate the ideas presented in the text. ... For the physics studen

Introduction to algorithms  3 ed.

Автор: Cormen, Thomas H., E
Название: Introduction to algorithms 3 ed.
ISBN: 0262033844 ISBN-13(EAN): 9780262033848
Издательство: MIT Press
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Цена: 27588.00 р.
Наличие на складе: Нет в наличии.

Описание: A new edition of the essential text and professional reference, with substantial new material on such topics as vEB trees, multithreaded algorithms, dynamic programming, and edge-base flow.

Network Science

Автор: Barab?si
Название: Network Science
ISBN: 1107076269 ISBN-13(EAN): 9781107076266
Издательство: Cambridge Academ
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Цена: 7762.00 р.
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Описание: Illustrated throughout in full colour, this pioneering textbook, spanning a wide range of disciplines from physics to the social sciences, is the only book needed for an introduction to network science. In modular format, with clear delineation between undergraduate and graduate material, its unique design is supported by extensive online resources.

Dynamic Fuzzy Machine Learning

Автор: Li, Fanzhang / Zhang, Li / Zhang, Zhao
Название: Dynamic Fuzzy Machine Learning
ISBN: 3110518708 ISBN-13(EAN): 9783110518702
Издательство: Walter de Gruyter
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Цена: 22439.00 р.
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Описание: Machine learning is widely used for data analysis. Dynamic fuzzy data are one of the most difficult types of data to analyse in the field of big data, cloud computing, the Internet of Things, and quantum information. At present, the processing of this kind of data is not very mature. The authors carried out more than 20 years of research, and show in this book their most important results. The seven chapters of the book are devoted to key topics such as dynamic fuzzy machine learning models, dynamic fuzzy self-learning subspace algorithms, fuzzy decision tree learning, dynamic concepts based on dynamic fuzzy sets, semi-supervised multi-task learning based on dynamic fuzzy data, dynamic fuzzy hierarchy learning, examination of multi-agent learning model based on dynamic fuzzy logic. This book can be used as a reference book for senior college students and graduate students as well as college teachers and scientific and technical personnel involved in computer science, artificial intelligence, machine learning, automation, data analysis, mathematics, management, cognitive science, and finance. It can be also used as the basis for teaching the principles of dynamic fuzzy learning.

Mathematical models and algorithms for power system optimization :

Автор: Fan, Mingtian,
Название: Mathematical models and algorithms for power system optimization :
ISBN: 0128132310 ISBN-13(EAN): 9780128132319
Издательство: Elsevier Science
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Цена: 22570.00 р.
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Описание:

Mathematical Models and Algorithms for Power System Optimization helps readers build a thorough understanding of new technologies and world-class practices developed by the State Grid Corporation of China, the organization responsible for the world's largest power distribution network. This reference covers three areas: power operation planning, electric grid investment and operational planning and power system control. It introduces economic dispatching, generator maintenance scheduling, power flow, optimal load flow, reactive power planning, load frequency control and transient stability, using mathematic models including optimization, dynamic, differential and difference equations.

  • Provides insights on the development of new mathematical models of power system optimization
  • Analyzes power systems comprehensively to create novel mathematic models and algorithms for issues related to the planning operation of power systems
  • Includes research on the optimization of power systems and related practical research projects carried out since 1981
Nature-Inspired Algorithms for Optimisation

Автор: Raymond Chiong
Название: Nature-Inspired Algorithms for Optimisation
ISBN: 3642101305 ISBN-13(EAN): 9783642101304
Издательство: Springer
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Цена: 36570.00 р.
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Описание: Nature-inspired algorithms have become popular because many real-world optimization problems have become increasingly large, complex and dynamic. This book covers the latest algorithms and important studies for tackling various kinds of optimization problems.

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.

Mathematical Biology I. An Introduction

Автор: Murray, James D.
Название: Mathematical Biology I. An Introduction
ISBN: 1475777094 ISBN-13(EAN): 9781475777093
Издательство: Springer
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Цена: 9781.00 р.
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Описание: Providing an in-depth look at the practical use of math modeling, it features exercises throughout that are drawn from a variety of bioscientific disciplines - population biology, developmental biology, physiology, epidemiology, and evolution, among others.

Hands-On Data Structures and Algorithms with Python 2 ed

Автор: Agarwal, Dr Basant, Baka, Benjamin
Название: Hands-On Data Structures and Algorithms with Python 2 ed
ISBN: 1788995570 ISBN-13(EAN): 9781788995573
Издательство: Неизвестно
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Цена: 8091.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Data structures help us to organize and align the data in a very efficient way. This book will surely help you to learn important and essential data structures through Python implementation for better understanding of the concepts.

Mathematical Methods in Engineering

Автор: Powers, Joseph M. (University of Notre Dame, Indiana) Sen, Mihir (University of Notre Dame, Indiana)
Название: Mathematical Methods in Engineering
ISBN: 1107037042 ISBN-13(EAN): 9781107037045
Издательство: Cambridge Academ
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Цена: 10138.00 р.
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Описание: This book is designed for engineering graduate students. It connects mathematics to a variety of methods used for engineering problems by walking the reader stepwise through examples that have been worked in detail, followed by numerous homework problems to reinforce learning and connect the subject matter to engineering applications.

Boosting: Foundations and Algorithms

Автор: Schapire Robert E., Freund Yoav
Название: Boosting: Foundations and Algorithms
ISBN: 0262526034 ISBN-13(EAN): 9780262526036
Издательство: MIT Press
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Цена: 6772.00 р.
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Описание:

An accessible introduction and essential reference for an approach to machine learning that creates highly accurate prediction rules by combining many weak and inaccurate ones.

Boosting is an approach to machine learning based on the idea of creating a highly accurate predictor by combining many weak and inaccurate "rules of thumb." A remarkably rich theory has evolved around boosting, with connections to a range of topics, including statistics, game theory, convex optimization, and information geometry. Boosting algorithms have also enjoyed practical success in such fields as biology, vision, and speech processing. At various times in its history, boosting has been perceived as mysterious, controversial, even paradoxical.

This book, written by the inventors of the method, brings together, organizes, simplifies, and substantially extends two decades of research on boosting, presenting both theory and applications in a way that is accessible to readers from diverse backgrounds while also providing an authoritative reference for advanced researchers. With its introductory treatment of all material and its inclusion of exercises in every chapter, the book is appropriate for course use as well.

The book begins with a general introduction to machine learning algorithms and their analysis; then explores the core theory of boosting, especially its ability to generalize; examines some of the myriad other theoretical viewpoints that help to explain and understand boosting; provides practical extensions of boosting for more complex learning problems; and finally presents a number of advanced theoretical topics. Numerous applications and practical illustrations are offered throughout.

Elements of Mathematical Ecology

Автор: Kot, Mark,
Название: Elements of Mathematical Ecology
ISBN: 0521001501 ISBN-13(EAN): 9780521001502
Издательство: Cambridge Academ
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Цена: 13779.00 р.
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Описание: An introduction to classical and modern mathematical models, methods, and issues in population ecology. Includes numerous line diagrams, relevant problems and supplementary mathematical and historical material that enhances understanding.


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