Guided Randomness in Optimization, Volume 1

Guided Randomness in Optimization, Volume 1 PDF Author: Maurice Clerc
Publisher: John Wiley & Sons
ISBN: 1848218052
Category : Computers
Languages : en
Pages : 316

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Book Description
The performance of an algorithm used depends on the GNA. This book focuses on the comparison of optimizers, it defines a stress-outcome approach which can be derived all the classic criteria (median, average, etc.) and other more sophisticated. Source-codes used for the examples are also presented, this allows a reflection on the "superfluous chance," succinctly explaining why and how the stochastic aspect of optimization could be avoided in some cases.

Guided Randomness in Optimization, Volume 1

Guided Randomness in Optimization, Volume 1 PDF Author: Maurice Clerc
Publisher: John Wiley & Sons
ISBN: 1848218052
Category : Computers
Languages : en
Pages : 316

Get Book Here

Book Description
The performance of an algorithm used depends on the GNA. This book focuses on the comparison of optimizers, it defines a stress-outcome approach which can be derived all the classic criteria (median, average, etc.) and other more sophisticated. Source-codes used for the examples are also presented, this allows a reflection on the "superfluous chance," succinctly explaining why and how the stochastic aspect of optimization could be avoided in some cases.

Multidisciplinary Design Optimization Supported by Knowledge Based Engineering

Multidisciplinary Design Optimization Supported by Knowledge Based Engineering PDF Author: Jaroslaw Sobieszczanski-Sobieski
Publisher: John Wiley & Sons
ISBN: 1118492129
Category : Technology & Engineering
Languages : en
Pages : 412

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Book Description
Multidisciplinary Design Optimization supported by Knowledge Based Engineering supports engineers confronting this daunting and new design paradigm. It describes methodology for conducting a system design in a systematic and rigorous manner that supports human creativity to optimize the design objective(s) subject to constraints and uncertainties. The material presented builds on decades of experience in Multidisciplinary Design Optimization (MDO) methods, progress in concurrent computing, and Knowledge Based Engineering (KBE) tools. Key features: Comprehensively covers MDO and is the only book to directly link this with KBE methods Provides a pathway through basic optimization methods to MDO methods Directly links design optimization methods to the massively concurrent computing technology Emphasizes real world engineering design practice in the application of optimization methods Multidisciplinary Design Optimization supported by Knowledge Based Engineering is a one-stop-shop guide to the state-of-the-art tools in the MDO and KBE disciplines for systems design engineers and managers. Graduate or post-graduate students can use it to support their design courses, and researchers or developers of computer-aided design methods will find it useful as a wide-ranging reference.

Algorithms for Optimization

Algorithms for Optimization PDF Author: Mykel J. Kochenderfer
Publisher: MIT Press
ISBN: 0262039427
Category : Computers
Languages : en
Pages : 521

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Book Description
A comprehensive introduction to optimization with a focus on practical algorithms for the design of engineering systems. This book offers a comprehensive introduction to optimization with a focus on practical algorithms. The book approaches optimization from an engineering perspective, where the objective is to design a system that optimizes a set of metrics subject to constraints. Readers will learn about computational approaches for a range of challenges, including searching high-dimensional spaces, handling problems where there are multiple competing objectives, and accommodating uncertainty in the metrics. Figures, examples, and exercises convey the intuition behind the mathematical approaches. The text provides concrete implementations in the Julia programming language. Topics covered include derivatives and their generalization to multiple dimensions; local descent and first- and second-order methods that inform local descent; stochastic methods, which introduce randomness into the optimization process; linear constrained optimization, when both the objective function and the constraints are linear; surrogate models, probabilistic surrogate models, and using probabilistic surrogate models to guide optimization; optimization under uncertainty; uncertainty propagation; expression optimization; and multidisciplinary design optimization. Appendixes offer an introduction to the Julia language, test functions for evaluating algorithm performance, and mathematical concepts used in the derivation and analysis of the optimization methods discussed in the text. The book can be used by advanced undergraduates and graduate students in mathematics, statistics, computer science, any engineering field, (including electrical engineering and aerospace engineering), and operations research, and as a reference for professionals.

Fundamentals of the New Artificial Intelligence

Fundamentals of the New Artificial Intelligence PDF Author: Toshinori Munakata
Publisher: Springer Science & Business Media
ISBN: 1846288398
Category : Computers
Languages : en
Pages : 266

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Book Description
The book covers the most essential and widely employed material in each area, particularly the material important for real-world applications. Our goal is not to cover every latest progress in the fields, nor to discuss every detail of various techniques that have been developed. New sections/subsections added in this edition are: Simulated Annealing (Section 3.7), Boltzmann Machines (Section 3.8) and Extended Fuzzy if-then Rules Tables (Sub-section 5.5.3). Also, numerous changes and typographical corrections have been made throughout the manuscript. The Preface to the first edition follows. General scope of the book Artificial intelligence (AI) as a field has undergone rapid growth in diversification and practicality. For the past few decades, the repertoire of AI techniques has evolved and expanded. Scores of newer fields have been added to the traditional symbolic AI. Symbolic AI covers areas such as knowledge-based systems, logical reasoning, symbolic machine learning, search techniques, and natural language processing. The newer fields include neural networks, genetic algorithms or evolutionary computing, fuzzy systems, rough set theory, and chaotic systems.

A Guide to Research Methodology

A Guide to Research Methodology PDF Author: Shyama Prasad Mukherjee
Publisher: CRC Press
ISBN: 100062739X
Category : Business & Economics
Languages : en
Pages : 289

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Book Description
Research Methodology is meant to provide a broad guideline to facilitate and steer the whole of a research activity in any discipline. With the ambit and amount of research increasing by the day, the need for Research Methodology is being widely appreciated. Against this backdrop, we notice the dearth of well-written books on the subject. A Guide to Research Methodology attempts a balance between the generic approach to research in any domain and the wide array of research methods which are to be used in carrying out different tasks in any research. Discussions on these research methods appropriate in various disciplines have focused on the research tasks, keeping in mind the fact that a single such task like a comparison among alternatives may involve several methods from seemingly distinct areas. Unique features of this volume, as will be evident to a discerning reader, include: A detailed discussion on problem areas for research in several domains An illustrative and ampliated list of research problems drawn from different disciplines which can be pursued by interested research workers A comprehensive delineation of Research Design supported by illustrations An elaborate engagement with models with a note on model uncertainty Focus on recent and emerging models, methods and techniques A novel treatment of data analysis where the nature of data and the objective(s) of analysis justify drawing upon a variety of techniques for analysis This book will serve the purpose of a pre-PhD or a Master-level course-work for students of any discipline with a basic knowledge of quantitative analysis. In fact, anyone aspiring to take up meaningful research work will find the content useful and interesting.

Basic Guide for Machine Learning Algorithms and Models

Basic Guide for Machine Learning Algorithms and Models PDF Author: Ms.G.Vanitha
Publisher: SK Research Group of Companies
ISBN: 936492469X
Category : Computers
Languages : en
Pages : 191

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Book Description
Ms.G.Vanitha, Associate Professor, Department of Information Technology, Bishop Heber College, Tiruchirappalli, Tamil Nadu, India. Dr.M.Kasthuri, Associate Professor, Department of Computer Science, Bishop Heber College, Tiruchirappalli, Tamil Nadu, India.

Swarm Intelligence Based Optimization

Swarm Intelligence Based Optimization PDF Author: Patrick Siarry
Publisher: Springer
ISBN: 3319503073
Category : Computers
Languages : en
Pages : 132

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Book Description
This book constitutes the thoroughly refereed post-conference proceedings of the Second International Conference on Swarm Intelligence Based Optimization, ICSIBO 2016, held in Mulhouse, France, in June 2016. The 9 full papers presented were carefully reviewed and selected from 20 submissions. They are centered around the following topics: theoretical advances of swarm intelligence metaheuristics; combinatorial discrete, binary, constrained, multi-objective, multi-modal, dynamic, noisy, and large scale optimization; artificial immune systems, particle swarms, ant colony, bacterial forging, artificial bees, fireflies algorithm; hybridization of algorithms; parallel/distributed computing, machine learning, data mining, data clustering, decision making and multi-agent systems based on swarm intelligence principles; adaptation and applications of swarm intelligence principles to real world problems in various domains.

Applied Quantum Mechanics

Applied Quantum Mechanics PDF Author: A. F. J. Levi
Publisher: Cambridge University Press
ISBN: 1009308068
Category : Technology & Engineering
Languages : en
Pages : 624

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Book Description
Featuring new coverage of quantum engineering and quantum information processing, the third edition of this bestselling textbook continues to provide students with a uniquely practical introduction to the fundamentals of quantum mechanics. It features straightforward explanations of quantum effects, suitable for readers from non-physics backgrounds; real-world engineering problems showcasing the practical application of theory to practice, providing a relevant and accessible introduction to cutting-edge quantum applications; over 60 accessible worked examples using Matlab, allowing students to deepen their understanding through computational exploration and visualization; and a new chapter on quantum engineering, introducing students to state-of-the-art concepts in quantum information processing and quantum device design. Updated throughout and supported online by downloadable Matlab code, exam questions, and solutions to over 150 homework problems for instructors, this is the ideal textbook for senior undergraduate and graduate students in applied science, engineering, and materials science studying a first course in quantum mechanics.

Guided Randomness in Optimization, Volume 1

Guided Randomness in Optimization, Volume 1 PDF Author: Maurice Clerc
Publisher: Wiley-ISTE
ISBN: 9781848218055
Category : Computers
Languages : en
Pages : 0

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Book Description
The performance of an algorithm used depends on the GNA. This book focuses on the comparison of optimizers, it defines a stress-outcome approach which can be derived all the classic criteria (median, average, etc.) and other more sophisticated. Source-codes used for the examples are also presented, this allows a reflection on the "superfluous chance," succinctly explaining why and how the stochastic aspect of optimization could be avoided in some cases.

Optimization

Optimization PDF Author: Rajesh Kumar Arora
Publisher: CRC Press
ISBN: 149872115X
Category : Business & Economics
Languages : en
Pages : 454

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Book Description
Choose the Correct Solution Method for Your Optimization ProblemOptimization: Algorithms and Applications presents a variety of solution techniques for optimization problems, emphasizing concepts rather than rigorous mathematical details and proofs. The book covers both gradient and stochastic methods as solution techniques for unconstrained and co