Artificial Neural Nets and Genetic Algorithms

Artificial Neural Nets and Genetic Algorithms

The 2003 edition of ICANNGA marks a milestone in this conference series, because it is the tenth year of its existence. The series began in 1993 with the inaugural conference at Innsbruck in Austria.

Author: David W. Pearson

Publisher: Springer Science & Business Media

ISBN: 9783709106464

Category: Computers

Page: 266

View: 450

The 2003 edition of ICANNGA marks a milestone in this conference series, because it is the tenth year of its existence. The series began in 1993 with the inaugural conference at Innsbruck in Austria. At that first conference, the organisers decided to organise a similar scientific meeting every two years. As a result, conferences were organised at Ales in France (1995), Norwich in England (1997), Portoroz in Slovenia (1999) and Prague in the Czech Republic (2001). It is a great honour that the conference is taking place in France for the second time. Each edition of ICANNGA has been special and had its own character. Not only that, participants have been able to sample the life and local culture in five different European coun tries. Originally limited to neural networks and genetic algorithms the conference has broadened its outlook over the past ten years and now includes papers on soft computing and artificial intelligence in general. This is one of the reasons why the reader will find papers on fuzzy logic and various other topics not directly related to neural networks or genetic algorithms included in these proceedings. We have, however, kept the same name, "International Conference on Artificial Neural Networks and Genetic Algorithms". All of the papers were sorted into one of six principal categories: neural network theory, neural network applications, genetic algorithm and evolutionary computation theory, genetic algorithm and evolutionary computation applications, fuzzy and soft computing theory, fuzzy and soft computing applications.
Categories: Computers

Nature inspired Methods in Chemometrics Genetic Algorithms and Artificial Neural Networks

Nature inspired Methods in Chemometrics  Genetic Algorithms and Artificial Neural Networks

This book contains contributions from experts in the field is divided in two sections (GA and ANN). In each part, tutorial chapters are included in which the theoretical bases of each technique are expertly (but simply) described.

Author: Riccardo Leardi

Publisher: Elsevier

ISBN: 0080522629

Category: Science

Page: 402

View: 295

In recent years Genetic Algorithms (GA) and Artificial Neural Networks (ANN) have progressively increased in importance amongst the techniques routinely used in chemometrics. This book contains contributions from experts in the field is divided in two sections (GA and ANN). In each part, tutorial chapters are included in which the theoretical bases of each technique are expertly (but simply) described. These are followed by application chapters in which special emphasis will be given to the advantages of the application of GA or ANN to that specific problem, compared to classical techniques, and to the risks connected with its misuse. This book is of use to all those who are using or are interested in GA and ANN. Beginners can focus their attentions on the tutorials, whilst the most advanced readers will be more interested in looking at the applications of the techniques. It is also suitable as a reference book for students. Subject matter is steadily increasing in importance Comparison of Genetic Algorithms (GA) and Artificial Neural Networks (ANN) with the classical techniques Suitable for both beginners and advanced researchers
Categories: Science

Artificial Neural Nets and Genetic Algorithms

Artificial Neural Nets and Genetic Algorithms

Proceedings of the International Conference in Prague, Czech Republic, 2001 Vera Kurkova, Nigel C. Steele, Roman Neruda, Miroslav Karny. J. Mäkilä, J.-P. Jalkanen Neural Network Combustion Optimisation in Naantali Power Plant .

Author: Vera Kurkova

Publisher: Springer Science & Business Media

ISBN: 9783709162309

Category: Computers

Page: 506

View: 950

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.
Categories: Computers

Artificial Neural Nets and Genetic Algorithms

Artificial Neural Nets and Genetic Algorithms

Kapsalis, A, Rayward-Smith, V.J., Smith, G.D.: Using Genetic Algorithms to Solve the Radio Link Frequency Assignment Problem. Proc. of the Second Int. Conf. on Artificial Neural Networks and Genetic Algorithms, pp.37-40, 1995.

Author: Andrej Dobnikar

Publisher: Springer Science & Business Media

ISBN: 9783709163849

Category: Computers

Page: 352

View: 325

From the contents: Neural networks – theory and applications: NNs (= neural networks) classifier on continuous data domains– quantum associative memory – a new class of neuron-like discrete filters to image processing – modular NNs for improving generalisation properties – presynaptic inhibition modelling for image processing application – NN recognition system for a curvature primal sketch – NN based nonlinear temporal-spatial noise rejection system – relaxation rate for improving Hopfield network – Oja's NN and influence of the learning gain on its dynamics Genetic algorithms – theory and applications: transposition: a biological-inspired mechanism to use with GAs (= genetic algorithms) – GA for decision tree induction – optimising decision classifications using GAs – scheduling tasks with intertask communication onto multiprocessors by GAs – design of robust networks with GA – effect of degenerate coding on GAs – multiple traffic signal control using a GA – evolving musical harmonisation – niched-penalty approach for constraint handling in GAs – GA with dynamic population size – GA with dynamic niche clustering for multimodal function optimisation Soft computing and uncertainty: self-adaptation of evolutionary constructed decision trees by information spreading – evolutionary programming of near optimal NNs
Categories: Computers

Artificial Neural Nets and Genetic Algorithms

Artificial Neural Nets and Genetic Algorithms

359-366, Pergamon Press, 1989 [4] Miller G., Todd P.M. and Hegde S.U., Designing Neural Networks Using Genetic Algorithms, Proc. of the third Intern. Conf. on Genetic Algorithms (ICGA), pp. 379–384, San Mateo (CA), 1989, [5] Schiffmann ...

Author: Rudolf F. Albrecht

Publisher: Springer Science & Business Media

ISBN: 9783709175330

Category: Computers

Page: 737

View: 885

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.
Categories: Computers

Artificial Neural Nets and Genetic Algorithms

Artificial Neural Nets and Genetic Algorithms

Evolutionary ANNs II The Baldwin Effect on the Evolution of Associative Memory A. Imada and K. Araki Using Embryology as an Alternative to Genetic Algorithms for Designing Artificial Neural Network Topologies C. MacLeod and G. Maxwell ...

Author: George D. Smith

Publisher: Springer Science & Business Media

ISBN: 9783709164921

Category: Computers

Page: 634

View: 862

This is the third in a series of conferences devoted primarily to the theory and applications of artificial neural networks and genetic algorithms. The first such event was held in Innsbruck, Austria, in April 1993, the second in Ales, France, in April 1995. We are pleased to host the 1997 event in the mediaeval city of Norwich, England, and to carryon the fine tradition set by its predecessors of providing a relaxed and stimulating environment for both established and emerging researchers working in these and other, related fields. This series of conferences is unique in recognising the relation between the two main themes of artificial neural networks and genetic algorithms, each having its origin in a natural process fundamental to life on earth, and each now well established as a paradigm fundamental to continuing technological development through the solution of complex, industrial, commercial and financial problems. This is well illustrated in this volume by the numerous applications of both paradigms to new and challenging problems. The third key theme of the series, therefore, is the integration of both technologies, either through the use of the genetic algorithm to construct the most effective network architecture for the problem in hand, or, more recently, the use of neural networks as approximate fitness functions for a genetic algorithm searching for good solutions in an 'incomplete' solution space, i.e. one for which the fitness is not easily established for every possible solution instance.
Categories: Computers

PGANET

PGANET

Author: Geoffrey H. Ballinger

Publisher:

ISBN: OCLC:606074439

Category:

Page:

View: 224

Categories:

Artificial Neural Networks ICANN 2002

Artificial Neural Networks     ICANN 2002

R.F. Albrecht, C. R. Reeves and N. C. Steele (eds), Artificial Neural Nets and Genetic Algorithms, Springer Verlag, 1993. 2. E. Blindauer, Méthodes d'encodage génétique de réseaux neuronaux, MSc thesis in Computer Science, Louis Pasteur ...

Author: Jose R. Dorronsoro

Publisher: Springer

ISBN: 9783540460848

Category: Computers

Page: 1384

View: 263

The International Conferences on Arti?cial Neural Networks, ICANN, have been held annually since 1991 and over the years have become the major European meeting in neural networks. This proceedings volume contains all the papers presented at ICANN 2002, the 12th ICANN conference, held in August 28– 30, 2002 at the Escuela T ́ecnica Superior de Inform ́atica of the Universidad Aut ́onoma de Madrid and organized by its Neural Networks group. ICANN 2002 received a very high number of contributions, more than 450. Almost all papers were revised by three independent reviewers, selected among the more than 240 serving at this year’s ICANN, and 221 papers were ?nally selected for publication in these proceedings (due to space considerations, quite a few good contributions had to be left out). I would like to thank the Program Committee and all the reviewers for the great collective e?ort and for helping us to have a high quality conference.
Categories: Computers