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Computational Intelligence [recurso electrónico] : for Engineering and Manufacturing / edited by Diego Andina, Duc Truong Pham.

Por: Colaborador(es): Tipo de material: TextoTextoEditor: Boston, MA : Springer US, 2007Descripción: XIII, 212 p. online resourceTipo de contenido:
  • text
Tipo de medio:
  • computer
Tipo de soporte:
  • recurso en línea
ISBN:
  • 9780387374529
  • 99780387374529
Tema(s): Formatos físicos adicionales: Printed edition:: Sin títuloClasificación CDD:
  • 004 23
Recursos en línea: En: Springer eBooksResumen: 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.
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Item type Current library Collection Call number Status Date due Barcode
Libros electrónicos Libros electrónicos CICY Libro electrónico Libro electrónico 004 (Browse shelf(Opens below)) Available

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.

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