Articles by "Artificial Intelligence"

Showing posts with label Artificial Intelligence. Show all posts

David Goldberg ... 432 pages - Publisher: Addison-Wesley Professional; 1st edition (January, 1989) ...
Language: English - ISBN-10: 0201157675 - ISBN-13: 978-0201157673 ...

This book brings together - in an informal and tutorial fashion - the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields. Major concepts are illustrated with running examples, and major algorithms are illustrated by Pascal computer programs. No prior knowledge of GAs or genetics is assumed, and only a minimum of computer programming and mathematics background is required.

Muhammet Ünal, Ayça Ak, V. Topuz, H. Erdal ... 88 pages - Publisher: Springer; (September, 2012) ...
Language: English - ISBN-10: 3642328997 - ISBN-13: 978-3642328992 ...

Artificial neural networks, genetic algorithms and the ant colony optimization algorithm have become a highly effective tool for solving hard optimization problems. As their popularity has increased, applications of these algorithms have grown in more than equal measure. While many of the books available on these subjects only provide a cursory discussion of theory, the present book gives special emphasis to the theoretical background that is behind these algorithms and their applications. Moreover, this book introduces a novel real time control algorithm, that uses genetic algorithm and ant colony optimization algorithms for optimizing PID controller parameters. In general, the present book represents a solid survey on artificial neural networks, genetic algorithms and the ant colony optimization algorithm and introduces novel practical elements related to the application of these methods to  process system control.

Hojjat Adeli, Kamal C. Sarma ... 222 pages - Publisher: Wiley; 1st edition (October, 2006) ...
Language: English - ISBN-10: 0470867337 - ISBN-13: 978-0470867334 ...

While the weight of a structure constitutes a significant part of the cost, a minimum weight design is not necessarily the minimum cost design. Little attention in structural optimization has been paid to the cost optimization problem, particularly of realistic three-dimensional structures. Cost optimization is becoming a priority in all civil engineering projects, and the concept of Life-Cycle Costing is penetrating design, manufacturing and construction organizations.

In this groundbreaking book the authors present novel computational models for cost optimization of large scale, realistic structures, subjected to the actual constraints of commonly used design codes.
As the first book on the subject this book: Contains detailed step-by-step algorithms - Focuses on novel computing techniques such as genetic algorithms, fuzzy logic, and parallel computing - Covers both Allowable Stress Design (ASD) and Load and Resistance Factor Design (LRFD) codes. - Includes realistic design examples covering large-scale, high-rise building structures - Presents computational models that enable substantial cost savings in the design of structures. Fully automated structural design and cost optimization is where large-scale design technology is heading, thus Cost Optimization of Structures: Fuzzy Logic, Genetic Algorithms, and Parallel Computing will be of great interest to civil and structural engineers, mechanical engineers, structural design software developers, and architectural engineers involved in the design of structures and life-cycle cost optimisation. It is also a pioneering text for graduate students and researchers working in building design and structural optimization.

Fred W. Glover, Gary A. Kochenberger ... 570 pages - Publisher: Springer; 1st edition (January, 2003) ...
Language: English - ISBN-10: 1402072635 - ISBN-13: 978-1402072635 ...

This book provides both the research and practitioner communities with a comprehensive coverage of the metaheuristic methodologies that have proven to be successful in a wide variety of real-world problem settings. Moreover, it is these metaheuristic strategies that hold particular promise for success in the future. The various chapters serve as stand alone presentations giving both the necessary background underpinnings as well as practical guides for implementation.

Xin-She Yang, Zhihua Cui, Renbin Xiao, Amir Hossein Gandomi and Mehmet Karamanoglu ... 450 pages - Publisher: Elsevier; 1st edition (June, 2013) ... Language: English - ISBN-10: 1493301365 - ISBN-13: 978-1493301362 ... 

Swarm Intelligence and bio-inspired computation have become increasing popular in the last two decades. Bio-inspired algorithms such as ant colony algorithms, bat algorithms, bee algorithms, firefly algorithms, cuckoo search and particle swarm optimization have been applied in almost every area of science and engineering with a dramatic increase of number of relevant publications. This book reviews the latest developments in swarm intelligence and bio-inspired computation from both the theory and application side, providing a complete resource that analyzes and discusses the latest and future trends in research directions. It can help new researchers to carry out timely research and inspire readers to develop new algorithms. With its impressive breadth and depth, this book will be useful for advanced undergraduate students, PhD students and lecturers in computer science, engineering and science as well as researchers and engineers. * Focuses on the introduction and analysis of key algorithms * Includes case studies for real-world applications * Contains a balance of theory and applications, so readers who are interested in either algorithm or applications will all benefit from this timely book.

Maurice Clerc, Bijaya Ketan Panigrahi, Yuhui Shi, Meng-Hiot Lim ... 
544 pages - Publisher: Springer;  (January, 2011) ... Language: English - ISBN-10: 3642173896 - ISBN-13: 978-3642173899.

From nature, we observe swarming behavior in the form of ant colonies, bird flocking, animal herding, honey bees, swarming of bacteria, and many more.  It is only in recent years that researchers have taken notice of such natural swarming systems as culmination of some form of innate collective intelligence, albeit swarm intelligence (SI) - a metaphor that inspires a myriad of computational problem-solving techniques.  In computational intelligence, swarm-like algorithms have been successfully applied to solve many real-world problems in engineering and sciences. This handbook volume serves as a useful foundational as well as consolidatory state-of-art collection of articles in the field from various researchers around the globe.  It has a rich collection of contributions pertaining to the theoretical and empirical study of single and multi-objective variants of swarm intelligence based algorithms like particle swarm optimization (PSO), ant colony optimization (ACO), bacterial foraging optimization algorithm (BFOA), honey bee social foraging algorithms, and harmony search (HS).  With chapters describing various applications of SI techniques in real-world engineering problems, this handbook can be a valuable resource for researchers and practitioners, giving an in-depth flavor of what SI is capable of achieving.

Aboul Ella Hassanien, Eid Emary ... 228 pages - Publisher: CRC Press; (November, 2015) ... Language: English - ISBN-10: 1498741061 - ISBN-13: 978-1498741064.

Swarm Intelligence: Principles, Advances, and Applications delivers in-depth coverage of bat, artificial fish swarm, firefly, cuckoo search, flower pollination, artificial bee colony, wolf search, and gray wolf optimization algorithms. The book begins with a brief introduction to mathematical optimization, addressing basic concepts related to swarm intelligence, such as randomness, random walks, and chaos theory. The text then: * Describes the various swarm intelligence optimization methods, standardizing the variants, hybridizations, and algorithms whenever possible * Discusses variants that focus more on binary, discrete, constrained, adaptive, and chaotic versions of the swarm optimizers * Depicts real-world applications of the individual optimizers, emphasizing variable selection and fitness function design * Details the similarities, differences, weaknesses, and strengths of each swarm optimization method * Draws parallels between the operators and searching manners of the different algorithms. Swarm Intelligence: Principles, Advances, and Applications presents a comprehensive treatment of modern swarm intelligence optimization methods, complete with illustrative examples and an extendable MATLAB® package for feature selection in wrapper mode applied on different data sets with benchmarking using different evaluation criteria. The book provides beginners with a solid foundation of swarm intelligence fundamentals, and offers experts valuable insight into new directions and hybridizations.

Marco Dorigo, Mauro Birattari, Christian Blum, Maurice Clerc, Thomas Stützle, Alan Winfield ... 416 pages - Publisher: Springer; (October, 2008) ... Language: English - ISBN-10: 3540875263 - ISBN-13: 978-3540875260.

This book constitutes the refereed proceedings of the 6th International Workshop on Ant Colony Optimization and Swarm Intelligence, ANTS 2008, held in Brussels, Belgium, in September 2008. The 17 revised full papers, 24 revised short papers, and 10 extended abstracts presented were carefully reviewed and selected from 91 submissions. The papers cover theoretical and foundational aspects of computational intelligence and related disciplines with special focus on swarm intelligence and are devoted to behavioral models of social insects and new algorithmic approaches, empirical and theoretical research in swarm intelligence, applications such as ant colony optimization or particle swarm optimization, and theoretical and experimental research in swarm robotics systems.

The series of biannual international conferences “ANTS – International C- ference on Ant Colony Optimization and Swarm Intelligence”, now in its sixth edition, was started ten years ago, with the organization of ANTS’98. As some readers might recall, the first edition of ANTS was titled “ANTS’98 – From Ant Colonies to Artificial Ants: First International Workshop on Ant Colony Op- mization. ” In fact, at that time the focus was mainly on ant colony optimization (ACO), the first swarm intelligence algorithm to go beyond a pure scientific interest and to enter the realm of real-world applications. Interestingly, in the ten years after the first edition there has been a gr- ing interest not only for ACO, but for a number of other studies that belong more generally to the area of swarmintelligence. The rapid growth of the swarm intelligence field is attested by a number of indicators. First, the number of s- missions and participants to the ANTS conferences has steadily increased over the years. Second, a number of international conferences in computational - intelligence and related disciplines organize workshops on subjects such as swarm intelligence, ant algorithms, ant colony optimization, and particle swarm op- mization. Third, IEEE startedorganizing,in 2003, the IEEE SwarmIntelligence Symposium (in order to maintain unity in this growing field, we are currently establishing a cooperation agreement between IEEE SISandANTSsoastohave 1 IEEE SIS in odd years and ANTS in even years). Last, the Swarm Intelligence journal was born.

Avi Ostfeld ... 352 pages - Publisher: InTech; 1st edition (February, 2011) ...
Language: English - ISBN-10: N/A - ISBN-13: 978-9533071572 ...

Ants communicate information by leaving pheromone tracks. A moving ant leaves, in varying quantities, some pheromone on the ground to mark its way. While an isolated ant moves essentially at random, an ant encountering a previously laid trail is able to detect it and decide with high probability to follow it, thus reinforcing the track with its own pheromone. The collective behavior that emerges is thus a positive feedback: where the more the ants following a track, the more attractive that track becomes for being followed; thus the probability with which an ant chooses a path increases with the number of ants that previously chose the same path. This elementary ant's behavior inspired the development of ant colony optimization by Marco Dorigo in 1992, constructing a meta-heuristic stochastic combinatorial computational methodology belonging to a family of related meta-heuristic methods such as simulated annealing, Tabu search and genetic algorithms. This book covers in twenty chapters state of the art methods and applications of utilizing ant colony optimization algorithms. New methods and theory such as multi colony ant algorithm based upon a new pheromone arithmetic crossover and a repulsive operator, new findings on ant colony convergence, and a diversity of engineering and science applications from transportation, water resources, electrical and computer science disciplines are presented.

Christine Solnon ... 320 pages - Publisher: Wiley-ISTE; (May, 2010) - Language: English - ISBN-10: 1848211309 - ISBN-13: 978-1848211308.

Ant colony optimization is a metaheuristic which has been successfully applied to a wide range of combinatorial optimization problems. The author describes this metaheuristic and studies its efficiency for solving some hard combinatorial problems, with a specific focus on constraint programming. The text is organized into three parts. The first part introduces constraint programming, which provides high level features to declaratively model problems by means of constraints. It describes the main existing approaches for solving constraint satisfaction problems, including complete tree search approaches and metaheuristics, and shows how they can be integrated within constraint programming languages.

The second part describes the ant colony optimization metaheuristic and illustrates its capabilities on different constraint satisfaction problems. The third part shows how the ant colony may be integrated within a constraint programming language, thus combining the expressive power of constraint programming languages, to describe problems in a declarative way, and the solving power of ant colony optimization to efficiently solve these problems.

Konstantinos L. Katsifarakis ... 174 pages - Publisher: WIT Press; (June, 2012) ... Language: English - ISBN-10: 1845646649 - ISBN-13: 978-1845646646.

With the population of our planet exceeding seven billion, funds for infrastructure works being limited worldwide, and climate change affecting water resources, their optimal development and management is literally vital. This volume deals with application of some non-traditional optimization techniques to hydraulics, hydrology and water resources management and aims at helping scientists dealing with these issues to reach the best decisions.

Jonas Mockus ... 322 pages - Publisher: Springer; (November, 2013) ... Language: English - ISBN-10: 1461371147 - ISBN-13: 978-1461371144

This book shows how the Bayesian Approach (BA) improves well­ known heuristics by randomizing and optimizing their parameters. That is the Bayesian Heuristic Approach (BHA). The ten in-depth examples are designed to teach Operations Research using Internet. Each example is a simple representation of some impor­ tant family of real-life problems. The accompanying software can be run by remote Internet users. The supporting web-sites include software for Java, C++, and other lan­ guages. A theoretical setting is described in which one can discuss a Bayesian adaptive choice of heuristics for discrete and global optimization prob­ lems. The techniques are evaluated in the spirit of the average rather than the worst case analysis. In this context, "heuristics" are understood to be an expert opinion defining how to solve a family of problems of dis­crete or global optimization. The term "Bayesian Heuristic Approach" means that one defines a set of heuristics and fixes some prior distribu­ tion on the results obtained. By applying BHA one is looking for the heuristic that reduces the average deviation from the global optimum. The theoretical discussions serve as an introduction to examples that are the main part of the book. All the examples are interconnected. Dif­ ferent examples illustrate different points of the general subject. How­ ever, one can consider each example separately, too.

Simon Haykin ... 936 pages - Publisher: PHIL; 3rd edition (2010) ... Language: English - ISBN-10: 8131763773 - ISBN-13: 978-8131763773 ...

The third edition of this classic book presents a comprehensive treatment of neural networks and learning machines. The book has been revised extensively to provide an up-to-date treatment of the subject.

Xiaolei Wang, Xiao-Zhi Gao, Kai Zenger ... 88 pages - Publisher: Springer; (September, 2014) ...
Language: English - ISBN-10: 3319083554 - ISBN-13: 978-3319083551 ...

This brief provides a detailed introduction, discussion and bibliographic review of the nature1-inspired optimization algorithm called Harmony Search. It uses a large number of simulation results to demonstrate the advantages of Harmony Search and its variants and also their drawbacks. The authors show how weaknesses can be amended by hybridization with other optimization methods. The Harmony Search Method with Applications will be of value to researchers in computational intelligence in demonstrating the state of the art of research on an algorithm of current interest. It also helps researchers and practitioners of electrical and computer engineering more generally in acquainting themselves with this method of vector-based optimization.

Sandhya Samarasinghe ... 570 pages - Publisher: Auerbach Publications; (September, 2006) ... Language: English - ISBN-10: 084933375X - ISBN-13: 978-0849333750.

In response to the exponentially increasing need to analyze vast amounts of data, Neural Networks for Applied Sciences and Engineering: From Fundamentals to Complex Pattern Recognition provides scientists with a simple but systematic introduction to neural networks. Beginning with an introductory discussion on the role of neural networks in scientific data analysis, this book provides a solid foundation of basic neural network concepts. It contains an overview of neural network architectures for practical data analysis followed by extensive step-by-step coverage on linear networks, as well as, multi-layer perceptron for nonlinear prediction and classification explaining all stages of processing and model development illustrated through practical examples and case studies. Later chapters present an extensive coverage on Self Organizing Maps for nonlinear data clustering, recurrent networks for linear nonlinear time series forecasting, and other network types suitable for scientific data analysis. With an easy to understand format using extensive graphical illustrations and multidisciplinary scientific context, this book fills the gap in the market for neural networks for multi-dimensional scientific data, and relates neural networks to statistics. Features: Explains neural networks in a multi-disciplinary context § Uses extensive graphical illustrations to explain complex mathematical concepts for quick and easy understanding § Examines in-depth neural networks for linear and nonlinear prediction, classification, clustering and forecasting § Illustrates all stages of model development and interpretation of results, including data preprocessing, data dimensionality reduction, input selection, model development and validation, model uncertainty assessment, sensitivity analyses on inputs, errors and model parameters. Sandhya Samarasinghe obtained her MSc in Mechanical Engineering from Lumumba University in Russia and an MS and PhD in Engineering from Virginia Tech, USA. Her neural networks research focuses on theoretical understanding and advancements as well as practical implementations.

John A. Flores ... 410 pages - Publisher: Nova Science Publishers; (September 30, 2011) ...
Language: English - ISBN-10: 1613242859 - ISBN-13: 978-1613242858 ...

This book gathers the most current research from across the globe in the study of artificial neural networks. Topics discussed include artificial neural networks in environmental sciences and chemical engineering; application of artificial neural networks in the development of pharamceutical microemulsions; massive-training artificial neural networks for supervised enhancement/suppression of lesions/patterns in medical images; evidences of new biophysical properties of microtubules; neural network applications in modern induction machine control systems and wavelet neural networks.

Robert A. Dunne ... 288 pages - Publisher: Wiley-Interscience; 1st edition (July 16, 2007) ...
Language: English - ISBN-10: 0471741086 - ISBN-13: 978-0471741084 ...

An accessible and up-to-date treatment featuring the connection between neural networks and statistics
A Statistical Approach to Neural Networks for Pattern Recognition presents a statistical treatment of the Multilayer Perceptron (MLP), which is the most widely used of the neural network models.

This book aims to answer questions that arise when statisticians are first confronted with this type of model, such as: How robust is the model to outliers? - Could the model be made more robust? - Which points will have a high leverage? - What are good starting values for the fitting algorithm?

Thorough answers to these questions and many more are included, as well as worked examples and selected problems for the reader. Discussions on the use of MLP models with spatial and spectral data are also included. Further treatment of highly important principal aspects of the MLP are provided, such as the robustness of the model in the event of outlying or atypical data; the influence and sensitivity curves of the MLP; why the MLP is a fairly robust model; and modifications to make the MLP more robust. The author also provides clarification of several misconceptions that are prevalent in existing neural network literature.

Throughout the book, the MLP model is extended in several directions to show that a statistical modeling approach can make valuable contributions, and further exploration for fitting MLP models is made possible via the R and S-PLUS® codes that are available on the book's related Web site. A Statistical Approach to Neural Networks for Pattern Recognition successfully connects logistic regression and linear discriminant analysis, thus making it a critical reference and self-study guide for students and professionals alike in the fields of mathematics, statistics, computer science, and electrical engineering.

Xin-She Yang ... 300 pages - Publisher: Elsevier; 1st edition (March, 2014) ... 
Language: English - ISBN-10: 0124167438 - ISBN-13: 978-0124167438 ...

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.

B. H. Topping ... 
Volume I: 653 pages - Publisher: Springer; Reprint of the original 1st (1992) edition (December 3, 2010)
Language: English - ISBN-10: 9048142016 - ISBN-13: 978-9048142019

Volume II: 354 pages - Publisher: Springer; Reprint of the original 1st (1992) edition (December 8, 2010)
Language: English - ISBN-10: 9048142024 - ISBN-13: 978-9048142026

This volume and its companion volume includes the edited versions of the principal lectures and selected papers presented at the NATO Advanced Study Institute on Optimization and Decision Support Systems in Civil Engineering. The Institute was held in the Department of Civil Engineering at Heriot-Watt University, Edinburgh from June 25th to July 6th 1989 and was attended by eighty participants from Universities and Research Institutes around the world. A number of practising civil and structural engineers also attended. The lectures and papers have been divided into two volumes to reflect the dual themes of the Institute namely Optimization and Decision Support Systems in Civil Engineering. Planning for this ASI commenced in late 1986 when Andrew Templeman and I discussed developments in the use of the systems approach in civil engineering. A little later it became clear that much of this approach could be realised through the use of knowledge-based systems and artificial intelligence techniques. Both Don Grierson and John Gero indicated at an early stage how important it would be to include knowledge-based systems within the scope of the Institute. The title of the Institute could have been: 'Civil Engineering Systems' as this would have reflected the range of systems applications to civil engineering problems considered by the Institute. These volumes therefore reflect the full range of these problems including: structural analysis and design; water resources engineering; geotechnical engineering; transportation and environmental engineering.

Kurt Marti ... 368 pages - Publisher: Springer; 3rd edition (February, 2015) ... Language: English - ISBN-10: 3662462133 - ISBN-13: 978-3662462133 ...

This book examines optimization problems that in practice involve random model parameters. It details the computation of robust optimal solutions, i.e., optimal solutions that are insensitive with respect to random parameter variations, where appropriate deterministic substitute problems are needed. Based on the probability distribution of the random data and using decision theoretical concepts, optimization problems under stochastic uncertainty are converted into appropriate deterministic substitute problems.Due to the probabilities and expectations involved, the book also shows how to apply approximative solution techniques. Several deterministic and stochastic approximation methods are provided: Taylor expansion methods, regression and response surface methods (RSM), probability inequalities, multiple linearization of survival/failure domains, discretization methods, convex approximation/deterministic descent directions/efficient points, stochastic approximation and gradient procedures and differentiation formulas for probabilities and expectations. In the third edition, this book further develops stochastic optimization methods. In particular, it now shows how to apply stochastic optimization methods to the approximate solution of important concrete problems arising in engineering, economics and operations research.

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