Multi Objective Optimization In Theory And Practice Ii Metaheuristic Algorithms

Download Multi Objective Optimization In Theory And Practice Ii Metaheuristic Algorithms full books in PDF, epub, and Kindle. Read online Multi Objective Optimization In Theory And Practice Ii Metaheuristic Algorithms ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!

Multi-Objective Optimization in Theory and Practice II: Metaheuristic Algorithms

Author : André A. Keller
Publisher : Bentham Science Publishers
ISBN 13 : 1681087065
Total Pages : 310 pages
Book Rating : 4.6/5 (81 download)

DOWNLOAD NOW!

Book Synopsis Multi-Objective Optimization in Theory and Practice II: Metaheuristic Algorithms by : André A. Keller

Download or read book Multi-Objective Optimization in Theory and Practice II: Metaheuristic Algorithms written by André A. Keller and published by Bentham Science Publishers. This book was released on 2019-03-28 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multi-Objective Optimization in Theory and Practice is a simplified two-part approach to multi-objective optimization (MOO) problems. This second part focuses on the use of metaheuristic algorithms in more challenging practical cases. The book includes ten chapters that cover several advanced MOO techniques. These include the determination of Pareto-optimal sets of solutions, metaheuristic algorithms, genetic search algorithms and evolution strategies, decomposition algorithms, hybridization of different metaheuristics, and many-objective (more than three objectives) optimization and parallel computation. The final section of the book presents information about the design and types of fifty test problems for which the Pareto-optimal front is approximated. For each of them, the package NSGA-II is used to approximate the Pareto-optimal front. It is an essential handbook for students and teachers involved in advanced optimization courses in engineering, information science and mathematics degree programs.

Multi-Objective Optimization in Theory and Practice I: Classical Methods

Author : Andre A. Keller
Publisher : Bentham Science Publishers
ISBN 13 : 1681085682
Total Pages : 296 pages
Book Rating : 4.6/5 (81 download)

DOWNLOAD NOW!

Book Synopsis Multi-Objective Optimization in Theory and Practice I: Classical Methods by : Andre A. Keller

Download or read book Multi-Objective Optimization in Theory and Practice I: Classical Methods written by Andre A. Keller and published by Bentham Science Publishers. This book was released on 2017-12-13 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multi-Objective Optimization in Theory and Practice is a traditional two-part approach to solving multi-objective optimization (MOO) problems namely the use of classical methods and evolutionary algorithms. This first book is devoted to classical methods including the extended simplex method by Zeleny and preference-based techniques. This part covers three main topics through nine chapters. The first topic focuses on the design of such MOO problems, their complexities including nonlinearities and uncertainties, and optimality theory. The second topic introduces the founding solving methods including the extended simplex method to linear MOO problems and weighting objective methods. The third topic deals with particular structures of MOO problems, such as mixed-integer programming, hierarchical programming, fuzzy logic programming, and bimatrix games. Multi-Objective Optimization in Theory and Practice is a user-friendly book with detailed, illustrated calculations, examples, test functions, and small-size applications in Mathematica® (among other mathematical packages) and from scholarly literature. It is an essential handbook for students and teachers involved in advanced optimization courses in engineering, information science, and mathematics degree programs.

Metaheuristic Algorithms

Author : Gai-Ge Wang
Publisher : CRC Press
ISBN 13 : 1040000347
Total Pages : 470 pages
Book Rating : 4.0/5 (4 download)

DOWNLOAD NOW!

Book Synopsis Metaheuristic Algorithms by : Gai-Ge Wang

Download or read book Metaheuristic Algorithms written by Gai-Ge Wang and published by CRC Press. This book was released on 2024-04-03 with total page 470 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces the theory and applications of metaheuristic algorithms. It also provides methods for solving practical problems in such fields as software engineering, image recognition, video networks, and in the oceans. In the theoretical section, the book introduces the information feedback model, learning-based intelligent optimization, dynamic multi-objective optimization, and multi-model optimization. In the applications section, the book presents applications of optimization algorithms to neural architecture search, fuzz testing, oceans, and image processing. The neural architecture search chapter introduces the latest NAS method. The fuzz testing chapter uses multi-objective optimization and ant colony optimization to solve the seed selection and energy allocation problems in fuzz testing. In the ocean chapter, deep learning methods such as CNN, transformer, and attention-based methods are used to describe ENSO prediction and image processing for marine fish identification, and to provide an overview of traditional classification methods and deep learning methods. Rich in examples, this book will be a great resource for students, scholars, and those interested in metaheuristic algorithms, as well as professional practitioners and researchers working on related topics.

Discrete Diversity and Dispersion Maximization

Author : Rafael Martí
Publisher : Springer Nature
ISBN 13 : 3031383109
Total Pages : 350 pages
Book Rating : 4.0/5 (313 download)

DOWNLOAD NOW!

Book Synopsis Discrete Diversity and Dispersion Maximization by : Rafael Martí

Download or read book Discrete Diversity and Dispersion Maximization written by Rafael Martí and published by Springer Nature. This book was released on 2024-01-06 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book demonstrates the metaheuristic methodologies that apply to maximum diversity problems to solve them. Maximum diversity problems arise in many practical settings from facility location to social network analysis and constitute an important class of NP-hard problems in combinatorial optimization. In fact, this volume presents a “missing link” in the combinatorial optimization-related literature. In providing the basic principles and fundamental ideas of the most successful methodologies for discrete optimization, this book allows readers to create their own applications for other discrete optimization problems. Additionally, the book is designed to be useful and accessible to researchers and practitioners in management science, industrial engineering, economics, and computer science, while also extending value to non-experts in combinatorial optimization. Owed to the tutorials presented in each chapter, this book may be used in a master course, a doctoral seminar, or as supplementary to a primary text in upper undergraduate courses. The chapters are divided into three main sections. The first section describes a metaheuristic methodology in a tutorial style, offering generic descriptions that, when applied, create an implementation of the methodology for any optimization problem. The second section presents the customization of the methodology to a given diversity problem, showing how to go from theory to application in creating a heuristic. The final part of the chapters is devoted to experimentation, describing the results obtained with the heuristic when solving the diversity problem. Experiments in the book target the so-called MDPLIB set of instances as a benchmark to evaluate the performance of the methods.

Multi-Objective Optimization in Computational Intelligence: Theory and Practice

Author : Thu Bui, Lam
Publisher : IGI Global
ISBN 13 : 1599045001
Total Pages : 496 pages
Book Rating : 4.5/5 (99 download)

DOWNLOAD NOW!

Book Synopsis Multi-Objective Optimization in Computational Intelligence: Theory and Practice by : Thu Bui, Lam

Download or read book Multi-Objective Optimization in Computational Intelligence: Theory and Practice written by Thu Bui, Lam and published by IGI Global. This book was released on 2008-05-31 with total page 496 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multi-objective optimization (MO) is a fast-developing field in computational intelligence research. Giving decision makers more options to choose from using some post-analysis preference information, there are a number of competitive MO techniques with an increasingly large number of MO real-world applications. Multi-Objective Optimization in Computational Intelligence: Theory and Practice explores the theoretical, as well as empirical, performance of MOs on a wide range of optimization issues including combinatorial, real-valued, dynamic, and noisy problems. This book provides scholars, academics, and practitioners with a fundamental, comprehensive collection of research on multi-objective optimization techniques, applications, and practices.

Multi-Objective Combinatorial Optimization Problems and Solution Methods

Author : Mehdi Toloo
Publisher : Academic Press
ISBN 13 : 0128238003
Total Pages : 316 pages
Book Rating : 4.1/5 (282 download)

DOWNLOAD NOW!

Book Synopsis Multi-Objective Combinatorial Optimization Problems and Solution Methods by : Mehdi Toloo

Download or read book Multi-Objective Combinatorial Optimization Problems and Solution Methods written by Mehdi Toloo and published by Academic Press. This book was released on 2022-02-09 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multi-Objective Combinatorial Optimization Problems and Solution Methods discusses the results of a recent multi-objective combinatorial optimization achievement that considered metaheuristic, mathematical programming, heuristic, hyper heuristic and hybrid approaches. In other words, the book presents various multi-objective combinatorial optimization issues that may benefit from different methods in theory and practice. Combinatorial optimization problems appear in a wide range of applications in operations research, engineering, biological sciences and computer science, hence many optimization approaches have been developed that link the discrete universe to the continuous universe through geometric, analytic and algebraic techniques. This book covers this important topic as computational optimization has become increasingly popular as design optimization and its applications in engineering and industry have become ever more important due to more stringent design requirements in modern engineering practice. Presents a collection of the most up-to-date research, providing a complete overview of multi-objective combinatorial optimization problems and applications Introduces new approaches to handle different engineering and science problems, providing the field with a collection of related research not already covered in the primary literature Demonstrates the efficiency and power of the various algorithms, problems and solutions, including numerous examples that illustrate concepts and algorithms

Handbook of Nature-Inspired Optimization Algorithms: The State of the Art

Author : Ali Wagdy Mohamed
Publisher : Springer Nature
ISBN 13 : 3031075161
Total Pages : 220 pages
Book Rating : 4.0/5 (31 download)

DOWNLOAD NOW!

Book Synopsis Handbook of Nature-Inspired Optimization Algorithms: The State of the Art by : Ali Wagdy Mohamed

Download or read book Handbook of Nature-Inspired Optimization Algorithms: The State of the Art written by Ali Wagdy Mohamed and published by Springer Nature. This book was released on 2022-09-03 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents recent contributions and significant development, advanced issues, and challenges. In real-world problems and applications, most of the optimization problems involve different types of constraints. These problems are called constrained optimization problems (COPs). The optimization of the constrained optimization problems is considered a challenging task since the optimum solution(s) must be feasible. In their original design, evolutionary algorithms (EAs) are able to solve unconstrained optimization problems effectively. As a result, in the past decade, many researchers have developed a variety of constraint handling techniques, incorporated into (EAs) designs, to counter this deficiency. The main objective for this book is to make available a self-contained collection of modern research addressing the general constrained optimization problems in many real-world applications using nature-inspired optimization algorithms. This book is suitable for a graduate class on optimization, but will also be useful for interested senior students working on their research projects.

Scalar and Vector Risk in the General Framework of Portfolio Theory

Author : Stanislaus Maier-Paape
Publisher : Springer Nature
ISBN 13 : 3031333217
Total Pages : 236 pages
Book Rating : 4.0/5 (313 download)

DOWNLOAD NOW!

Book Synopsis Scalar and Vector Risk in the General Framework of Portfolio Theory by : Stanislaus Maier-Paape

Download or read book Scalar and Vector Risk in the General Framework of Portfolio Theory written by Stanislaus Maier-Paape and published by Springer Nature. This book was released on 2023-09-01 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is the culmination of the authors’ industry-academic collaboration in the past several years. The investigation is largely motivated by bank balance sheet management problems. The main difference between a bank balance sheet management problem and a typical portfolio optimization problem is that the former involves multiple risks. The related theoretical investigation leads to a significant extension of the scope of portfolio theories. The book combines practitioners’ perspectives and mathematical rigor. For example, to guide the bank managers to trade off different Pareto efficient points, the topological structure of the Pareto efficient set is carefully analyzed. Moreover, on top of computing solutions, the authors focus the investigation on the qualitative properties of those solutions and their financial meanings. These relations, such as the role of duality, are most useful in helping bank managers to communicate their decisions to the different stakeholders. Finally, bank balance sheet management problems of varying levels of complexity are discussed to illustrate how to apply the central mathematical results. Although the primary motivation and application examples in this book are focused in the area of bank balance sheet management problems, the range of applications of the general portfolio theory is much wider. As a matter of fact, most financial problems involve multiple types of risks. Thus, the book is a good reference for financial practitioners in general and students who are interested in financial applications. This book can also serve as a nice example of a case study for applied mathematicians who are interested in engaging in industry-academic collaboration.

Non-Convex Multi-Objective Optimization

Author : Panos M. Pardalos
Publisher : Springer
ISBN 13 : 3319610074
Total Pages : 196 pages
Book Rating : 4.3/5 (196 download)

DOWNLOAD NOW!

Book Synopsis Non-Convex Multi-Objective Optimization by : Panos M. Pardalos

Download or read book Non-Convex Multi-Objective Optimization written by Panos M. Pardalos and published by Springer. This book was released on 2017-07-27 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent results on non-convex multi-objective optimization problems and methods are presented in this book, with particular attention to expensive black-box objective functions. Multi-objective optimization methods facilitate designers, engineers, and researchers to make decisions on appropriate trade-offs between various conflicting goals. A variety of deterministic and stochastic multi-objective optimization methods are developed in this book. Beginning with basic concepts and a review of non-convex single-objective optimization problems; this book moves on to cover multi-objective branch and bound algorithms, worst-case optimal algorithms (for Lipschitz functions and bi-objective problems), statistical models based algorithms, and probabilistic branch and bound approach. Detailed descriptions of new algorithms for non-convex multi-objective optimization, their theoretical substantiation, and examples for practical applications to the cell formation problem in manufacturing engineering, the process design in chemical engineering, and business process management are included to aide researchers and graduate students in mathematics, computer science, engineering, economics, and business management.

Metaheuristics for Multiobjective Optimisation

Author : Xavier Gandibleux
Publisher : Springer Science & Business Media
ISBN 13 : 3642171443
Total Pages : 252 pages
Book Rating : 4.6/5 (421 download)

DOWNLOAD NOW!

Book Synopsis Metaheuristics for Multiobjective Optimisation by : Xavier Gandibleux

Download or read book Metaheuristics for Multiobjective Optimisation written by Xavier Gandibleux and published by Springer Science & Business Media. This book was released on 2012-08-27 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: The success of metaheuristics on hard single-objective optimization problems is well recognized today. However, many real-life problems require taking into account several conflicting points of view corresponding to multiple objectives. The use of metaheuristic optimization techniques for multi-objective problems is the subject of this volume. The book includes selected surveys, tutorials and state-of-the-art research papers in this field, which were first presented at a free workshop jointly organized by the French working group on Multi-objective Mathematical Programming (PM2O) and the EURO working group on Metaheuristics in December 2002. It is the first book which considers both various metaheuristics and various kind of problems (e.g. combinatorial problems, real situations, non-linear problems) applied to multiple objective optimization. Metaheuristics used include: genetic algorithms, ant colony optimization, simulated annealing, scatter search, etc. Problems concern timetabling, vehicle routing, and more. Methodological aspects, such as quality evaluation, are also covered.

Theory and Principled Methods for the Design of Metaheuristics

Author : Yossi Borenstein
Publisher : Springer Science & Business Media
ISBN 13 : 3642332064
Total Pages : 270 pages
Book Rating : 4.6/5 (423 download)

DOWNLOAD NOW!

Book Synopsis Theory and Principled Methods for the Design of Metaheuristics by : Yossi Borenstein

Download or read book Theory and Principled Methods for the Design of Metaheuristics written by Yossi Borenstein and published by Springer Science & Business Media. This book was released on 2013-12-19 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt: Metaheuristics, and evolutionary algorithms in particular, are known to provide efficient, adaptable solutions for many real-world problems, but the often informal way in which they are defined and applied has led to misconceptions, and even successful applications are sometimes the outcome of trial and error. Ideally, theoretical studies should explain when and why metaheuristics work, but the challenge is huge: mathematical analysis requires significant effort even for simple scenarios and real-life problems are usually quite complex. In this book the editors establish a bridge between theory and practice, presenting principled methods that incorporate problem knowledge in evolutionary algorithms and other metaheuristics. The book consists of 11 chapters dealing with the following topics: theoretical results that show what is not possible, an assessment of unsuccessful lines of empirical research; methods for rigorously defining the appropriate scope of problems while acknowledging the compromise between the class of problems to which a search algorithm is applied and its overall expected performance; the top-down principled design of search algorithms, in particular showing that it is possible to design algorithms that are provably good for some rigorously defined classes; and, finally, principled practice, that is reasoned and systematic approaches to setting up experiments, metaheuristic adaptation to specific problems, and setting parameters. With contributions by some of the leading researchers in this domain, this book will be of significant value to scientists, practitioners, and graduate students in the areas of evolutionary computing, metaheuristics, and computational intelligence.

Metaheuristics for Dynamic Optimization

Author : Enrique Alba
Publisher : Springer
ISBN 13 : 3642306659
Total Pages : 400 pages
Book Rating : 4.6/5 (423 download)

DOWNLOAD NOW!

Book Synopsis Metaheuristics for Dynamic Optimization by : Enrique Alba

Download or read book Metaheuristics for Dynamic Optimization written by Enrique Alba and published by Springer. This book was released on 2012-08-11 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is an updated effort in summarizing the trending topics and new hot research lines in solving dynamic problems using metaheuristics. An analysis of the present state in solving complex problems quickly draws a clear picture: problems that change in time, having noise and uncertainties in their definition are becoming very important. The tools to face these problems are still to be built, since existing techniques are either slow or inefficient in tracking the many global optima that those problems are presenting to the solver technique. Thus, this book is devoted to include several of the most important advances in solving dynamic problems. Metaheuristics are the more popular tools to this end, and then we can find in the book how to best use genetic algorithms, particle swarm, ant colonies, immune systems, variable neighborhood search, and many other bioinspired techniques. Also, neural network solutions are considered in this book. Both, theory and practice have been addressed in the chapters of the book. Mathematical background and methodological tools in solving this new class of problems and applications are included. From the applications point of view, not just academic benchmarks are dealt with, but also real world applications in logistics and bioinformatics are discussed here. The book then covers theory and practice, as well as discrete versus continuous dynamic optimization, in the aim of creating a fresh and comprehensive volume. This book is targeted to either beginners and experienced practitioners in dynamic optimization, since we took care of devising the chapters in a way that a wide audience could profit from its contents. We hope to offer a single source for up-to-date information in dynamic optimization, an inspiring and attractive new research domain that appeared in these last years and is here to stay.

Theory and Practice of Natural Computing

Author : Carlos Martín-Vide
Publisher : Springer
ISBN 13 : 3319710699
Total Pages : 319 pages
Book Rating : 4.3/5 (197 download)

DOWNLOAD NOW!

Book Synopsis Theory and Practice of Natural Computing by : Carlos Martín-Vide

Download or read book Theory and Practice of Natural Computing written by Carlos Martín-Vide and published by Springer. This book was released on 2017-12-12 with total page 319 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 6th International Conference,on Theory and Practice of Natural Computing, TPNC 2017, held in Prague, Czech Republic, December 2017. The 22 full papers presented in this book, together with one invited talk, werecarefully reviewed and selected from 39 submissions. The papers are organized around the following topical sections: applications of natural computing; evolutionary computation; fuzzy logic; Molecular computation; neural networks; quantum computing.

Deep Statistical Comparison for Meta-heuristic Stochastic Optimization Algorithms

Author : Tome Eftimov
Publisher : Springer Nature
ISBN 13 : 3030969177
Total Pages : 141 pages
Book Rating : 4.0/5 (39 download)

DOWNLOAD NOW!

Book Synopsis Deep Statistical Comparison for Meta-heuristic Stochastic Optimization Algorithms by : Tome Eftimov

Download or read book Deep Statistical Comparison for Meta-heuristic Stochastic Optimization Algorithms written by Tome Eftimov and published by Springer Nature. This book was released on 2022-06-11 with total page 141 pages. Available in PDF, EPUB and Kindle. Book excerpt: Focusing on comprehensive comparisons of the performance of stochastic optimization algorithms, this book provides an overview of the current approaches used to analyze algorithm performance in a range of common scenarios, while also addressing issues that are often overlooked. In turn, it shows how these issues can be easily avoided by applying the principles that have produced Deep Statistical Comparison and its variants. The focus is on statistical analyses performed using single-objective and multi-objective optimization data. At the end of the book, examples from a recently developed web-service-based e-learning tool (DSCTool) are presented. The tool provides users with all the functionalities needed to make robust statistical comparison analyses in various statistical scenarios. The book is intended for newcomers to the field and experienced researchers alike. For newcomers, it covers the basics of optimization and statistical analysis, familiarizing them with the subject matter before introducing the Deep Statistical Comparison approach. Experienced researchers can quickly move on to the content on new statistical approaches. The book is divided into three parts: Part I: Introduction to optimization, benchmarking, and statistical analysis – Chapters 2-4. Part II: Deep Statistical Comparison of meta-heuristic stochastic optimization algorithms – Chapters 5-7. Part III: Implementation and application of Deep Statistical Comparison – Chapter 8.

Engineering Optimization

Author : Singiresu S. Rao
Publisher : John Wiley & Sons
ISBN 13 : 1119454794
Total Pages : 832 pages
Book Rating : 4.1/5 (194 download)

DOWNLOAD NOW!

Book Synopsis Engineering Optimization by : Singiresu S. Rao

Download or read book Engineering Optimization written by Singiresu S. Rao and published by John Wiley & Sons. This book was released on 2019-10-30 with total page 832 pages. Available in PDF, EPUB and Kindle. Book excerpt: The revised and updated new edition of the popular optimization book for engineers The thoroughly revised and updated fifth edition of Engineering Optimization: Theory and Practice offers engineers a guide to the important optimization methods that are commonly used in a wide range of industries. The author—a noted expert on the topic—presents both the classical and most recent optimizations approaches. The book introduces the basic methods and includes information on more advanced principles and applications. The fifth edition presents four new chapters: Solution of Optimization Problems Using MATLAB; Metaheuristic Optimization Methods; Multi-Objective Optimization Methods; and Practical Implementation of Optimization. All of the book's topics are designed to be self-contained units with the concepts described in detail with derivations presented. The author puts the emphasis on computational aspects of optimization and includes design examples and problems representing different areas of engineering. Comprehensive in scope, the book contains solved examples, review questions and problems. This important book: Offers an updated edition of the classic work on optimization Includes approaches that are appropriate for all branches of engineering Contains numerous practical design and engineering examples Offers more than 140 illustrative examples, 500 plus references in the literature of engineering optimization, and more than 500 review questions and answers Demonstrates the use of MATLAB for solving different types of optimization problems using different techniques Written for students across all engineering disciplines, the revised edition of Engineering Optimization: Theory and Practice is the comprehensive book that covers the new and recent methods of optimization and reviews the principles and applications.

Decision Sciences

Author : Raghu Nandan Sengupta
Publisher : CRC Press
ISBN 13 : 1482282569
Total Pages : 1042 pages
Book Rating : 4.4/5 (822 download)

DOWNLOAD NOW!

Book Synopsis Decision Sciences by : Raghu Nandan Sengupta

Download or read book Decision Sciences written by Raghu Nandan Sengupta and published by CRC Press. This book was released on 2016-11-30 with total page 1042 pages. Available in PDF, EPUB and Kindle. Book excerpt: This handbook is an endeavour to cover many current, relevant, and essential topics related to decision sciences in a scientific manner. Using this handbook, graduate students, researchers, as well as practitioners from engineering, statistics, sociology, economics, etc. will find a new and refreshing paradigm shift as to how these topics can be put to use beneficially. Starting from the basics to advanced concepts, authors hope to make the readers well aware of the different theoretical and practical ideas, which are the focus of study in decision sciences nowadays. It includes an excellent bibliography/reference/journal list, information about a variety of datasets, illustrated pseudo-codes, and discussion of future trends in research. Covering topics ranging from optimization, networks and games, multi-objective optimization, inventory theory, statistical methods, artificial neural networks, times series analysis, simulation modeling, decision support system, data envelopment analysis, queueing theory, etc., this reference book is an attempt to make this area more meaningful for varied readers. Noteworthy features of this handbook are in-depth coverage of different topics, solved practical examples, unique datasets for a variety of examples in the areas of decision sciences, in-depth analysis of problems through colored charts, 3D diagrams, and discussions about software.

Advances and Trends in Artificial Intelligence. From Theory to Practice

Author : Franz Wotawa
Publisher : Springer
ISBN 13 : 3030229998
Total Pages : 868 pages
Book Rating : 4.0/5 (32 download)

DOWNLOAD NOW!

Book Synopsis Advances and Trends in Artificial Intelligence. From Theory to Practice by : Franz Wotawa

Download or read book Advances and Trends in Artificial Intelligence. From Theory to Practice written by Franz Wotawa and published by Springer. This book was released on 2019-06-28 with total page 868 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed proceedings of the 32nd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2019, held in Graz, Austria, in July 2019. The 41 full papers and 32 short papers presented were carefully reviewed and selected from 151 submissions. The IEA/AIE 2019 conference will continue the tradition of emphasizing on applications of applied intelligent systems to solve real-life problems in all areas. These areas include engineering, science, industry, automation and robotics, business and finance, medicine and biomedicine, bioinformatics, cyberspace, and human-machine interactions. IEA/AIE 2019 will have a special focus on automated driving and autonomous systems and also contributions dealing with such systems or their verification and validation as well.