Genetic Algorithm And Variable Feed Forward Neural Networks

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Artificial Neural Nets and Genetic Algorithms

Author : Rudolf F. Albrecht
Publisher : Springer Science & Business Media
ISBN 13 : 370917533X
Total Pages : 752 pages
Book Rating : 4.7/5 (91 download)

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Book Synopsis Artificial Neural Nets and Genetic Algorithms by : Rudolf F. Albrecht

Download or read book Artificial Neural Nets and Genetic Algorithms written by Rudolf F. Albrecht and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 752 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial neural networks and genetic algorithms both are areas of research which have their origins in mathematical models constructed in order to gain understanding of important natural processes. By focussing on the process models rather than the processes themselves, significant new computational techniques have evolved which have found application in a large number of diverse fields. This diversity is reflected in the topics which are the subjects of contributions to this volume. There are contributions reporting theoretical developments in the design of neural networks, and in the management of their learning. In a number of contributions, applications to speech recognition tasks, control of industrial processes as well as to credit scoring, and so on, are reflected. Regarding genetic algorithms, several methodological papers consider how genetic algorithms can be improved using an experimental approach, as well as by hybridizing with other useful techniques such as tabu search. The closely related area of classifier systems also receives a significant amount of coverage, aiming at better ways for their implementation. Further, while there are many contributions which explore ways in which genetic algorithms can be applied to real problems, nearly all involve some understanding of the context in order to apply the genetic algorithm paradigm more successfully. That this can indeed be done is evidenced by the range of applications covered in this volume.

Adaptive and Natural Computing Algorithms

Author : Bernadete Ribeiro
Publisher : Springer Science & Business Media
ISBN 13 : 3211273891
Total Pages : 561 pages
Book Rating : 4.2/5 (112 download)

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Book Synopsis Adaptive and Natural Computing Algorithms by : Bernadete Ribeiro

Download or read book Adaptive and Natural Computing Algorithms written by Bernadete Ribeiro and published by Springer Science & Business Media. This book was released on 2005-12-12 with total page 561 pages. Available in PDF, EPUB and Kindle. Book excerpt: The ICANNGA series of Conferences has been organised since 1993 and has a long history of promoting the principles and understanding of computational intelligence paradigms within the scientific community and is a reference for established workers in this area. Starting in Innsbruck, in Austria (1993), then to Ales in Prance (1995), Norwich in England (1997), Portoroz in Slovenia (1999), Prague in the Czech Republic (2001) and finally Roanne, in France (2003), the ICANNGA series has established itself for experienced workers in the field. The series has also been of value to young researchers wishing both to extend their knowledge and experience and also to meet internationally renowned experts. The 2005 Conference, the seventh in the ICANNGA series, will take place at the University of Coimbra in Portugal, drawing on the experience of previous events, and following the same general model, combining technical sessions, including plenary lectures by renowned scientists, with tutorials.

Artificial Neural Nets and Genetic Algorithms

Author : David W. Pearson
Publisher : Springer Science & Business Media
ISBN 13 : 3709175356
Total Pages : 542 pages
Book Rating : 4.7/5 (91 download)

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Book Synopsis Artificial Neural Nets and Genetic Algorithms by : David W. Pearson

Download or read book Artificial Neural Nets and Genetic Algorithms written by David W. Pearson and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 542 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial neural networks and genetic algorithms both are areas of research which have their origins in mathematical models constructed in order to gain understanding of important natural processes. By focussing on the process models rather than the processes themselves, significant new computational techniques have evolved which have found application in a large number of diverse fields. This diversity is reflected in the topics which are subjects of the contributions to this volume. There are contributions reporting successful applications of the technology to the solution of industrial/commercial problems. This may well reflect the maturity of the technology, notably in the sense that 'real' users of modelling/prediction techniques are prepared to accept neural networks as a valid paradigm. Theoretical issues also receive attention, notably in connection with the radial basis function neural network. Contributions in the field of genetic algorithms reflect the wide range of current applications, including, for example, portfolio selection, filter design, frequency assignment, tuning of nonlinear PID controllers. These techniques are also used extensively for combinatorial optimisation problems.

From Natural to Artificial Neural Computation

Author : Jose Mira
Publisher : Springer Science & Business Media
ISBN 13 : 9783540594970
Total Pages : 1182 pages
Book Rating : 4.5/5 (949 download)

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Book Synopsis From Natural to Artificial Neural Computation by : Jose Mira

Download or read book From Natural to Artificial Neural Computation written by Jose Mira and published by Springer Science & Business Media. This book was released on 1995-05-24 with total page 1182 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume presents the proceedings of the International Workshop on Artificial Neural Networks, IWANN '95, held in Torremolinos near Malaga, Spain in June 1995. The book contains 143 revised papers selected from a wealth of submissions and five invited contributions; it covers all current aspects of neural computation and presents the state of the art of ANN research and applications. The papers are organized in sections on neuroscience, computational models of neurons and neural nets, organization principles, learning, cognitive science and AI, neurosimulators, implementation, neural networks for perception, and neural networks for communication and control.

Artificial Neural Nets and Genetic Algorithms

Author :
Publisher :
ISBN 13 :
Total Pages : 556 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Artificial Neural Nets and Genetic Algorithms by :

Download or read book Artificial Neural Nets and Genetic Algorithms written by and published by . This book was released on 1995 with total page 556 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Deep Learning and Neural Networks: Concepts, Methodologies, Tools, and Applications

Author : Management Association, Information Resources
Publisher : IGI Global
ISBN 13 : 1799804151
Total Pages : 1707 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Deep Learning and Neural Networks: Concepts, Methodologies, Tools, and Applications by : Management Association, Information Resources

Download or read book Deep Learning and Neural Networks: Concepts, Methodologies, Tools, and Applications written by Management Association, Information Resources and published by IGI Global. This book was released on 2019-10-11 with total page 1707 pages. Available in PDF, EPUB and Kindle. Book excerpt: Due to the growing use of web applications and communication devices, the use of data has increased throughout various industries. It is necessary to develop new techniques for managing data in order to ensure adequate usage. Deep learning, a subset of artificial intelligence and machine learning, has been recognized in various real-world applications such as computer vision, image processing, and pattern recognition. The deep learning approach has opened new opportunities that can make such real-life applications and tasks easier and more efficient. Deep Learning and Neural Networks: Concepts, Methodologies, Tools, and Applications is a vital reference source that trends in data analytics and potential technologies that will facilitate insight in various domains of science, industry, business, and consumer applications. It also explores the latest concepts, algorithms, and techniques of deep learning and data mining and analysis. Highlighting a range of topics such as natural language processing, predictive analytics, and deep neural networks, this multi-volume book is ideally designed for computer engineers, software developers, IT professionals, academicians, researchers, and upper-level students seeking current research on the latest trends in the field of deep learning.

Modeling Decisions for Artificial Intelligence

Author : Vicenç Torra
Publisher : Springer Science & Business Media
ISBN 13 : 3540737286
Total Pages : 511 pages
Book Rating : 4.5/5 (47 download)

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Book Synopsis Modeling Decisions for Artificial Intelligence by : Vicenç Torra

Download or read book Modeling Decisions for Artificial Intelligence written by Vicenç Torra and published by Springer Science & Business Media. This book was released on 2007-07-30 with total page 511 pages. Available in PDF, EPUB and Kindle. Book excerpt: Decision modeling is a key area in the developing field of AI, and this timely work connects researchers and professionals with the very latest research. It constitutes the refereed proceedings of the 4th International Conference on Modeling Decisions for Artificial Intelligence, held in Kitakyushu, Japan, in August 2007. The 42 revised full papers presented together with 4 invited lectures are devoted to theory and tools, as well as applications.

Fusion of Neural Networks, Fuzzy Systems and Genetic Algorithms

Author : Lakhmi C. Jain
Publisher : CRC Press
ISBN 13 : 1000722945
Total Pages : 366 pages
Book Rating : 4.0/5 (7 download)

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Book Synopsis Fusion of Neural Networks, Fuzzy Systems and Genetic Algorithms by : Lakhmi C. Jain

Download or read book Fusion of Neural Networks, Fuzzy Systems and Genetic Algorithms written by Lakhmi C. Jain and published by CRC Press. This book was released on 2020-01-29 with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial neural networks can mimic the biological information-processing mechanism in - a very limited sense. Fuzzy logic provides a basis for representing uncertain and imprecise knowledge and forms a basis for human reasoning. Neural networks display genuine promise in solving problems, but a definitive theoretical basis does not yet exist for their design. Fusion of Neural Networks, Fuzzy Systems and Genetic Algorithms integrates neural net, fuzzy system, and evolutionary computing in system design that enables its readers to handle complexity - offsetting the demerits of one paradigm by the merits of another. This book presents specific projects where fusion techniques have been applied. The chapters start with the design of a new fuzzy-neural controller. Remaining chapters discuss the application of expert systems, neural networks, fuzzy control, and evolutionary computing techniques in modern engineering systems. These specific applications include: direct frequency converters electro-hydraulic systems motor control toaster control speech recognition vehicle routing fault diagnosis Asynchronous Transfer Mode (ATM) communications networks telephones for hard-of-hearing people control of gas turbine aero-engines telecommunications systems design Fusion of Neural Networks, Fuzzy Systems and Genetic Algorithms covers the spectrum of applications - comprehensively demonstrating the advantages of fusion techniques in industrial applications.

An Introduction to Optimization

Author : Edwin K. P. Chong
Publisher : John Wiley & Sons
ISBN 13 : 0471654000
Total Pages : 497 pages
Book Rating : 4.4/5 (716 download)

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Book Synopsis An Introduction to Optimization by : Edwin K. P. Chong

Download or read book An Introduction to Optimization written by Edwin K. P. Chong and published by John Wiley & Sons. This book was released on 2004-04-05 with total page 497 pages. Available in PDF, EPUB and Kindle. Book excerpt: A modern, up-to-date introduction to optimization theory and methods This authoritative book serves as an introductory text to optimization at the senior undergraduate and beginning graduate levels. With consistently accessible and elementary treatment of all topics, An Introduction to Optimization, Second Edition helps students build a solid working knowledge of the field, including unconstrained optimization, linear programming, and constrained optimization. Supplemented with more than one hundred tables and illustrations, an extensive bibliography, and numerous worked examples to illustrate both theory and algorithms, this book also provides: * A review of the required mathematical background material * A mathematical discussion at a level accessible to MBA and business students * A treatment of both linear and nonlinear programming * An introduction to recent developments, including neural networks, genetic algorithms, and interior-point methods * A chapter on the use of descent algorithms for the training of feedforward neural networks * Exercise problems after every chapter, many new to this edition * MATLAB(r) exercises and examples * Accompanying Instructor's Solutions Manual available on request An Introduction to Optimization, Second Edition helps students prepare for the advanced topics and technological developments that lie ahead. It is also a useful book for researchers and professionals in mathematics, electrical engineering, economics, statistics, and business. An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department.

Artificial Neural Nets and Genetic Algorithms

Author : Vera Kurkova
Publisher : Springer Science & Business Media
ISBN 13 : 9783211836514
Total Pages : 528 pages
Book Rating : 4.8/5 (365 download)

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Book Synopsis Artificial Neural Nets and Genetic Algorithms by : Vera Kurkova

Download or read book Artificial Neural Nets and Genetic Algorithms written by Vera Kurkova and published by Springer Science & Business Media. This book was released on 2001-04-11 with total page 528 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first ICANNGA conference, devoted to biologically inspired computational paradigms, Neural Net works and Genetic Algorithms, was held in Innsbruck, Austria, in 1993. The meeting attracted researchers from all over Europe and further afield, who decided that this particular blend of topics should form a theme for a series of biennial conferences. The second meeting, held in Ales, France, in 1995, carried on the tradition set in Innsbruck of a relaxed and stimulating environment for the. exchange of ideas. The series has continued in Norwich, UK, in 1997, and Portoroz, Slovenia, in 1999. The Institute of Computer Science, Czech Academy of Sciences, is pleased to host the fifth conference in Prague. We have chosen the Liechtenstein palace under the Prague Castle as the conference site to enhance the traditionally good atmosphere of the meeting. There is an inspirational genius loci of the historical center of the city, where four hundred years ago a fruitful combination of theoretical and empirical method, through the collaboration of Johannes Kepler and Tycho de Brahe, led to the discovery of the laws of planetary orbits.

Foundations of Neural Networks, Fuzzy Systems, and Knowledge Engineering

Author : Nikola K. Kasabov
Publisher : Marcel Alencar
ISBN 13 : 0262112124
Total Pages : 581 pages
Book Rating : 4.2/5 (621 download)

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Book Synopsis Foundations of Neural Networks, Fuzzy Systems, and Knowledge Engineering by : Nikola K. Kasabov

Download or read book Foundations of Neural Networks, Fuzzy Systems, and Knowledge Engineering written by Nikola K. Kasabov and published by Marcel Alencar. This book was released on 1996 with total page 581 pages. Available in PDF, EPUB and Kindle. Book excerpt: Combines the study of neural networks and fuzzy systems with symbolic artificial intelligence (AI) methods to build comprehensive AI systems. Describes major AI problems (pattern recognition, speech recognition, prediction, decision-making, game-playing) and provides illustrative examples. Includes applications in engineering, business and finance.

Artificial Neural Networks in Cancer Diagnosis, Prognosis, and Patient Management

Author : R. N. G. Naguib
Publisher : CRC Press
ISBN 13 : 1420036386
Total Pages : 216 pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis Artificial Neural Networks in Cancer Diagnosis, Prognosis, and Patient Management by : R. N. G. Naguib

Download or read book Artificial Neural Networks in Cancer Diagnosis, Prognosis, and Patient Management written by R. N. G. Naguib and published by CRC Press. This book was released on 2001-06-22 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: The potential value of artificial neural networks (ANN) as a predictor of malignancy has begun to receive increased recognition. Research and case studies can be found scattered throughout a multitude of journals. Artificial Neural Networks in Cancer Diagnosis, Prognosis, and Patient Management brings together the work of top researchers - primaril

Computational Intelligence for Missing Data Imputation, Estimation, and Management: Knowledge Optimization Techniques

Author : Marwala, Tshilidzi
Publisher : IGI Global
ISBN 13 : 1605663379
Total Pages : 325 pages
Book Rating : 4.6/5 (56 download)

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Book Synopsis Computational Intelligence for Missing Data Imputation, Estimation, and Management: Knowledge Optimization Techniques by : Marwala, Tshilidzi

Download or read book Computational Intelligence for Missing Data Imputation, Estimation, and Management: Knowledge Optimization Techniques written by Marwala, Tshilidzi and published by IGI Global. This book was released on 2009-04-30 with total page 325 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book is for those who use data analysis to build decision support systems, particularly engineers, scientists and statisticians"--Provided by publisher.

NEURAL NETWORKS, FUZZY LOGIC AND GENETIC ALGORITHM

Author : S. RAJASEKARAN
Publisher : PHI Learning Pvt. Ltd.
ISBN 13 : 8120321863
Total Pages : 459 pages
Book Rating : 4.1/5 (23 download)

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Book Synopsis NEURAL NETWORKS, FUZZY LOGIC AND GENETIC ALGORITHM by : S. RAJASEKARAN

Download or read book NEURAL NETWORKS, FUZZY LOGIC AND GENETIC ALGORITHM written by S. RAJASEKARAN and published by PHI Learning Pvt. Ltd.. This book was released on 2003-01-01 with total page 459 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides comprehensive introduction to a consortium of technologies underlying soft computing, an evolving branch of computational intelligence. The constituent technologies discussed comprise neural networks, fuzzy logic, genetic algorithms, and a number of hybrid systems which include classes such as neuro-fuzzy, fuzzy-genetic, and neuro-genetic systems. The hybridization of the technologies is demonstrated on architectures such as Fuzzy-Back-propagation Networks (NN-FL), Simplified Fuzzy ARTMAP (NN-FL), and Fuzzy Associative Memories. The book also gives an exhaustive discussion of FL-GA hybridization. Every architecture has been discussed in detail through illustrative examples and applications. The algorithms have been presented in pseudo-code with a step-by-step illustration of the same in problems. The applications, demonstrative of the potential of the architectures, have been chosen from diverse disciplines of science and engineering. This book with a wealth of information that is clearly presented and illustrated by many examples and applications is designed for use as a text for courses in soft computing at both the senior undergraduate and first-year post-graduate engineering levels. It should also be of interest to researchers and technologists desirous of applying soft computing technologies to their respective fields of work.

Real-World Applications of Genetic Algorithms

Author : Olympia Roeva
Publisher : BoD – Books on Demand
ISBN 13 : 9535101463
Total Pages : 379 pages
Book Rating : 4.5/5 (351 download)

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Book Synopsis Real-World Applications of Genetic Algorithms by : Olympia Roeva

Download or read book Real-World Applications of Genetic Algorithms written by Olympia Roeva and published by BoD – Books on Demand. This book was released on 2012-03-07 with total page 379 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book addresses some of the most recent issues, with the theoretical and methodological aspects, of evolutionary multi-objective optimization problems and the various design challenges using different hybrid intelligent approaches. Multi-objective optimization has been available for about two decades, and its application in real-world problems is continuously increasing. Furthermore, many applications function more effectively using a hybrid systems approach. The book presents hybrid techniques based on Artificial Neural Network, Fuzzy Sets, Automata Theory, other metaheuristic or classical algorithms, etc. The book examines various examples of algorithms in different real-world application domains as graph growing problem, speech synthesis, traveling salesman problem, scheduling problems, antenna design, genes design, modeling of chemical and biochemical processes etc.

Blind Equalization in Neural Networks

Author : Liyi Zhang
Publisher : Walter de Gruyter GmbH & Co KG
ISBN 13 : 3110450291
Total Pages : 268 pages
Book Rating : 4.1/5 (14 download)

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Book Synopsis Blind Equalization in Neural Networks by : Liyi Zhang

Download or read book Blind Equalization in Neural Networks written by Liyi Zhang and published by Walter de Gruyter GmbH & Co KG. This book was released on 2017-12-18 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book begins with an introduction of blind equalization theory and its application in neural networks, then discusses the algorithms in recurrent networks, fuzzy networks and other frequently-studied neural networks. Each algorithm is accompanied by derivation, modeling and simulation, making the book an essential reference for electrical engineers, computer intelligence researchers and neural scientists.

Elements of Artificial Neural Networks

Author : Kishan Mehrotra
Publisher : MIT Press
ISBN 13 : 9780262133289
Total Pages : 376 pages
Book Rating : 4.1/5 (332 download)

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Book Synopsis Elements of Artificial Neural Networks by : Kishan Mehrotra

Download or read book Elements of Artificial Neural Networks written by Kishan Mehrotra and published by MIT Press. This book was released on 1997 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: Elements of Artificial Neural Networks provides a clearly organized general introduction, focusing on a broad range of algorithms, for students and others who want to use neural networks rather than simply study them. The authors, who have been developing and team teaching the material in a one-semester course over the past six years, describe most of the basic neural network models (with several detailed solved examples) and discuss the rationale and advantages of the models, as well as their limitations. The approach is practical and open-minded and requires very little mathematical or technical background. Written from a computer science and statistics point of view, the text stresses links to contiguous fields and can easily serve as a first course for students in economics and management. The opening chapter sets the stage, presenting the basic concepts in a clear and objective way and tackling important -- yet rarely addressed -- questions related to the use of neural networks in practical situations. Subsequent chapters on supervised learning (single layer and multilayer networks), unsupervised learning, and associative models are structured around classes of problems to which networks can be applied. Applications are discussed along with the algorithms. A separate chapter takes up optimization methods. The most frequently used algorithms, such as backpropagation, are introduced early on, right after perceptrons, so that these can form the basis for initiating course projects. Algorithms published as late as 1995 are also included. All of the algorithms are presented using block-structured pseudo-code, and exercises are provided throughout. Software implementing many commonly used neural network algorithms is available at the book's website. Transparency masters, including abbreviated text and figures for the entire book, are available for instructors using the text.