Algorithms from and for Nature and Life
Algorithms from and for Nature and Life

Author: Berthold Lausen

Publisher: Springer Science & Business Media

Published: 2013-08-28

Total Pages: 532

ISBN-13: 3319000357

DOWNLOAD EBOOK

This volume provides approaches and solutions to challenges occurring at the interface of research fields such as, e.g., data analysis, data mining and knowledge discovery, computer science, operations research, and statistics. In addition to theory-oriented contributions various application areas are included. Moreover, traditional classification research directions concerning network data, graphs, and social relationships as well as statistical musicology describe examples for current interest fields tackled by the authors. The book comprises a total of 55 selected papers presented at the Joint Conference of the German Classification Society (GfKl), the German Association for Pattern Recognition (DAGM), and the Symposium of the International Federation of Classification Societies (IFCS) in 2011.​

The Everyday Life of an Algorithm
The Everyday Life of an Algorithm

Author: Daniel Neyland

Publisher: Springer

Published: 2018-12-17

Total Pages: 154

ISBN-13: 303000578X

DOWNLOAD EBOOK

This open access book begins with an algorithm–a set of IF...THEN rules used in the development of a new, ethical, video surveillance architecture for transport hubs. Readers are invited to follow the algorithm over three years, charting its everyday life. Questions of ethics, transparency, accountability and market value must be grasped by the algorithm in a series of ever more demanding forms of experimentation. Here the algorithm must prove its ability to get a grip on everyday life if it is to become an ordinary feature of the settings where it is being put to work. Through investigating the everyday life of the algorithm, the book opens a conversation with existing social science research that tends to focus on the power and opacity of algorithms. In this book we have unique access to the algorithm’s design, development and testing, but can also bear witness to its fragility and dependency on others.

Probably Approximately Correct
Probably Approximately Correct

Author: Leslie Valiant

Publisher: Basic Books (AZ)

Published: 2013-06-04

Total Pages: 210

ISBN-13: 0465032710

DOWNLOAD EBOOK

Presenting a theory of the theoryless, a computer scientist provides a model of how effective behavior can be learned even in a world as complex as our own, shedding new light on human nature.

Clever Algorithms
Clever Algorithms

Author: Jason Brownlee

Publisher: Jason Brownlee

Published: 2011

Total Pages: 437

ISBN-13: 1446785068

DOWNLOAD EBOOK

This book provides a handbook of algorithmic recipes from the fields of Metaheuristics, Biologically Inspired Computation and Computational Intelligence that have been described in a complete, consistent, and centralized manner. These standardized descriptions were carefully designed to be accessible, usable, and understandable. Most of the algorithms described in this book were originally inspired by biological and natural systems, such as the adaptive capabilities of genetic evolution and the acquired immune system, and the foraging behaviors of birds, bees, ants and bacteria. An encyclopedic algorithm reference, this book is intended for research scientists, engineers, students, and interested amateurs. Each algorithm description provides a working code example in the Ruby Programming Language.

The Power of Algorithms
The Power of Algorithms

Author: Giorgio Ausiello

Publisher: Springer Science & Business Media

Published: 2013-11-08

Total Pages: 262

ISBN-13: 3642396526

DOWNLOAD EBOOK

To examine, analyze, and manipulate a problem to the point of designing an algorithm for solving it is an exercise of fundamental value in many fields. With so many everyday activities governed by algorithmic principles, the power, precision, reliability and speed of execution demanded by users have transformed the design and construction of algorithms from a creative, artisanal activity into a full-fledged science in its own right. This book is aimed at all those who exploit the results of this new science, as designers and as consumers. The first chapter is an overview of the related history, demonstrating the long development of ideas such as recursion and more recent formalizations such as computability. The second chapter shows how the design of algorithms requires appropriate techniques and sophisticated organization of data. In the subsequent chapters the contributing authors present examples from diverse areas – such as routing and networking problems, Web search, information security, auctions and games, complexity and randomness, and the life sciences – that show how algorithmic thinking offers practical solutions and also deepens domain knowledge. The contributing authors are top-class researchers with considerable academic and industrial experience; they are also excellent educators and communicators and they draw on this experience with enthusiasm and humor. This book is an excellent introduction to an intriguing domain and it will be enjoyed by undergraduate and postgraduate students in computer science, engineering, and mathematics, and more broadly by all those engaged with algorithmic thinking.

Metaheuristic Optimization: Nature-Inspired Algorithms Swarm and Computational Intelligence, Theory and Applications
Metaheuristic Optimization: Nature-Inspired Algorithms Swarm and Computational Intelligence, Theory and Applications

Author: Modestus O. Okwu

Publisher: Springer Nature

Published: 2020-11-13

Total Pages: 196

ISBN-13: 3030611116

DOWNLOAD EBOOK

This book exemplifies how algorithms are developed by mimicking nature. Classical techniques for solving day-to-day problems is time-consuming and cannot address complex problems. Metaheuristic algorithms are nature-inspired optimization techniques for solving real-life complex problems. This book emphasizes the social behaviour of insects, animals and other natural entities, in terms of converging power and benefits. Major nature-inspired algorithms discussed in this book include the bee colony algorithm, ant colony algorithm, grey wolf optimization algorithm, whale optimization algorithm, firefly algorithm, bat algorithm, ant lion optimization algorithm, grasshopper optimization algorithm, butterfly optimization algorithm and others. The algorithms have been arranged in chapters to help readers gain better insight into nature-inspired systems and swarm intelligence. All the MATLAB codes have been provided in the appendices of the book to enable readers practice how to solve examples included in all sections. This book is for experts in Engineering and Applied Sciences, Natural and Formal Sciences, Economics, Humanities and Social Sciences.

Nature-Inspired Optimization Algorithms
Nature-Inspired Optimization Algorithms

Author: Xin-She Yang

Publisher: Elsevier

Published: 2014-02-17

Total Pages: 277

ISBN-13: 0124167454

DOWNLOAD EBOOK

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

Nature-Inspired Optimization Algorithms for Fuzzy Controlled Servo Systems
Nature-Inspired Optimization Algorithms for Fuzzy Controlled Servo Systems

Author: Radu-Emil Precup

Publisher: Butterworth-Heinemann

Published: 2019-04-23

Total Pages: 148

ISBN-13: 0128163585

DOWNLOAD EBOOK

Nature-inspired Optimization Algorithms for Fuzzy Controlled Servo Systems explains fuzzy control in servo systems in a way that doesn't require any solid mathematical prerequisite. Analysis and design methodologies are covered, along with specific applications to servo systems and representative case studies. The theoretical approaches presented throughout the book are validated by the illustration of digital simulation and real-time experimental results. This book is a great resource for a wide variety of readers, including graduate students, engineers (designers, practitioners and researchers), and everyone who faces challenging control problems.

Nature-Inspired Computing
Nature-Inspired Computing

Author: Nazmul H. Siddique

Publisher: CRC Press

Published: 2017-05-19

Total Pages: 623

ISBN-13: 1482244837

DOWNLOAD EBOOK

Nature-Inspired Computing: Physics and Chemistry-Based Algorithms provides a comprehensive introduction to the methodologies and algorithms in nature-inspired computing, with an emphasis on applications to real-life engineering problems. The research interest for Nature-inspired Computing has grown considerably exploring different phenomena observed in nature and basic principles of physics, chemistry, and biology. The discipline has reached a mature stage and the field has been well-established. This endeavour is another attempt at investigation into various computational schemes inspired from nature, which are presented in this book with the development of a suitable framework and industrial applications. Designed for senior undergraduates, postgraduates, research students, and professionals, the book is written at a comprehensible level for students who have some basic knowledge of calculus and differential equations, and some exposure to optimization theory. Due to the focus on search and optimization, the book is also appropriate for electrical, control, civil, industrial and manufacturing engineering, business, and economics students, as well as those in computer and information sciences. With the mathematical and programming references and applications in each chapter, the book is self-contained, and can also serve as a reference for researchers and scientists in the fields of system science, natural computing, and optimization.

Nature-Inspired Optimization Algorithms
Nature-Inspired Optimization Algorithms

Author: Aditya Khamparia

Publisher: Walter de Gruyter GmbH & Co KG

Published: 2021-02-08

Total Pages: 201

ISBN-13: 311067615X

DOWNLOAD EBOOK

This book will focus on the involvement of data mining and intelligent computing methods for recent advances in Biomedical applications and algorithms of nature-inspired computing for Biomedical systems. The proposed meta heuristic or nature-inspired techniques should be an enhanced, hybrid, adaptive or improved version of basic algorithms in terms of performance and convergence metrics. In this exciting and emerging interdisciplinary area a wide range of theory and methodologies are being investigated and developed to tackle complex and challenging problems. Today, analysis and processing of data is one of big focuses among researchers community and information society. Due to evolution and knowledge discovery of natural computing, related meta heuristic or bio-inspired algorithms have gained increasing popularity in the recent decade because of their significant potential to tackle computationally intractable optimization dilemma in medical, engineering, military, space and industry fields. The main reason behind the success rate of nature inspired algorithms is their capability to solve problems. The nature inspired optimization techniques provide adaptive computational tools for the complex optimization problems and diversified engineering applications. Tentative Table of Contents/Topic Coverage: - Neural Computation - Evolutionary Computing Methods - Neuroscience driven AI Inspired Algorithms - Biological System based algorithms - Hybrid and Intelligent Computing Algorithms - Application of Natural Computing - Review and State of art analysis of Optimization algorithms - Molecular and Quantum computing applications - Swarm Intelligence - Population based algorithm and other optimizations