Computational Intelligence : For Engineering and Manufacturing

Unlike traditional computing, Computational Intelligence is tolerant of imprecise information, partial truth and uncertainty. This book presents a selected collection of contributions on a focused treatment of important elements of CI, centred on its key element: learning. All the contributors of this volume have direct bearing with this issue. From fundamentals to advanced systems as Multilayer Perceptron Artificial Neural Networks (ANN-MLP), Radial Basis Function Networks (RBF) and its relations with Fuzzy Sets and Support Vector Machines theory; and on to several critical applications in Engineering and Manufacturing. These are among applications where CI has excellent potential. This volume has specially taken Neural Networks, key elements of CI, to the next level. Both novice and expert readers can benefit from this timely addition to CI based literature. Towards that goal, the editors and the authors have made critical contributions and succeeded. They have paved the road for learning paradigms towards the solution of many real-world problems. "This book presents a selected collection of contributions on a focused treatment of important elements of Computational Intelligence. Unlike traditional comp- ing, Computational Intelligence (CI) is tolerant of imprecise information, partial truthanduncertainty. TheprinciplecomponentsofCIthatcurrentlyhavefrequent applicationinEngineeringandManufacturingare:NeuralNetworks(NN), fuzzy logic(FL)andSupportVectorMachines(SVM). InCI, NNandSVMareconcerned withlearning, whileFLwithimprecisionandreasoning.? This volume mainly covers a key element of Computational Intelligence learning. All the contributions in this volume have a direct relevance to neural? networklearning fromneuralcomputingfundamentalstoadvancednetworkssuch asMultilayerPerceptrons(MLP), RadialBasisFunctionNetworks(RBF), andtheir relations with fuzzy set and support vector machines theory. The book also d- cussesdifferentapplicationsinEngineeringandManufacturing. Theseareamong applicationswhereCIhaveexcellentpotentialsforuse. Bothnoviceandexpertreadersshouldfindthisbookausefulreferenceinthefield ofComputationalIntelligence. Theeditorsandtheauthorshopetohavecontributed tothefieldbypavingthewayforlearningparadigmstosolvereal-worldproblems D. Andina xi ACKNOWLEDGEMENTS This document has been produced with the financial assistance of the European Community, ALFAprojectII-0026-FA. Theviewsexpressedhereinarethoseof theAuthorsandcanthereforeinnowaybetakentoreflecttheofficialopinionof theEuropeanCommunity. TheeditorswishtothankDrA. AfifyofCardiffUniversityandMrA. Jevticof theTechnicalUniversityofMadridfortheirsupportandhelpfulcommentsduring therevisionofthistext. The editors also wish to thank Nagib Callaos, President of the International Institute of Informatics and Systemics, IIIS, for his permission and freedom to reproduceinChapters2and4ofthisbookcontentsfromthebookbyD. Andina and F. Ballesteros (Eds), "Recent Advances in Neural Networks" Ed. IIIS press, ILL, USA(2000). xiii CHAPTER 1 SOFTCOMPUTINGANDITSAPPLICATIONS INENGINEERINGANDMANUFACTURE D.T. PHAM, P.T.N. PHAM, M.S. PACKIANATHER, A.A. AFIFY ManufacturingEngineeringCentre, CardiffUniversity, CardiffCF243AA, UnitedKingdom INTRODUCTION Softcomputingisarecenttermforacomputingparadigmthathasbeeninexistence foralmostfiftyyears. Thischapterreviewsfivesoftcomputingtools. Theyare: knowledge-based systems, fuzzy logic, inductive learning, neural networks and genetic algorithms. All of these tools have found many practical applications. Examples of applications in engineering and manufacture will be given in the chapter. 1. KNOWLEDGE-BASEDSYSTEMS Knowledge-basedsystems, orexpertsystems, arecomputerprogramsembodying knowledge about a narrow domain for solving problems related to that domain."--Font no determinada "Unlike traditional computing, Computational Intelligence is tolerant of imprecise information, partial truth and uncertainty. This book presents a selected collection of contributions on a focused treatment of important elements of CI, centred on its key element: learning. All the contributors of this volume have direct bearing with this issue. From fundamentals to advanced systems as Multilayer Perceptron Artificial Neural Networks (ANN-MLP), Radial Basis Function Networks (RBF) and its relations with Fuzzy Sets and Support Vector Machines theory; and on to several critical applications in Engineering and Manufacturing. These are among applications where CI have excellent potential." "This volume has specially taken Neural Networks, key elements of CI, to the next level. Both novice and expert readers can benefit from this timely addition to CI based literature. Towards that goal, the editors and the authors have made critical contributions and succeeded. They have paved the road for learning paradigms towards the solution of many real-world problems." -- Book Jacket

Unlike traditional computing, Computational Intelligence is tolerant of imprecise information, partial truth and uncertainty. This book presents a selected collection of contributions on a focused treatment of important elements of CI, centred on its key element: learning. All the contributors of this volume have direct bearing with this issue. From fundamentals to advanced systems as Multilayer Perceptron Artificial Neural Networks (ANN-MLP), Radial Basis Function Networks (RBF) and its relations with Fuzzy Sets and Support Vector Machines theory; and on to several critical applications in Engineering and Manufacturing. These are among applications where CI have excellent potential.

This volume has specially taken Neural Networks, key elements of CI, to the next level. Both novice and expert readers can benefit from this timely addition to CI based literature. Towards that goal, the editors and the authors have made critical contributions and succeeded. They have paved the road for learning paradigms towards the solution of many real-world problems.

Soft Computing and its Applications in Engineering and Manufacture....Pages 1-38 Neural Networks Historical Review....Pages 39-65 Artificial Neural Networks....Pages 67-92 Application of Neural Networks....Pages 93-108 Radial Basis Function Networks and their Application in Communication Systems....Pages 109-130 Biological Clues for Up-to-Date Artificial Neurons....Pages 131-146 Support Vector Machines....Pages 147-191 Fractals as Pre-Processing Tool for Computational Intelligence Application....Pages 193-212 Computational Intelligence is tolerant of imprecise information, partial truth and uncertainty. This book presents a selected collection of contributions on a focused treatment of important elements of CI, centred on its key element: learning. This book presents novel applications and real world applications working in Manufacturing and Engineering, and it sets a basis for understanding Domotic and Production Methods of the XXI Century.