Knowledge Extraction with Neural Networks

Iveta Mrazova

ISBN 10: 3844329412 / ISBN 13: 9783844329414

Verlag: LAP LAMBERT Academic Publishing Okt 2011, 2011

Beschreibung

This item is printed on demand - Print on Demand Titel. Neuware -Recent turbulences of global economy impose strong requirements on efficiency, flexibility, and reliability of new products and services. Unfortunately, for most techniques applicable to the design of complex adaptive systems ¿ artificial neural networks, fuzzy logic, cluster analysis, etc. ¿ it is still complicated to interpret what they are actually doing ¿ especially when processing large sets of high-dimensional data. Yet understanding and correct interpretation of the knowledge extracted by the applied model represent decisive issues for the ability to detect significant, e.g. novel input patterns, to identify their characteristic features and to assess their future development. This book provides new means to handle these problems with artificial neural networks of the Back-Propagation type. Two case studies involving image classification and analysis of economical data provided by the World Bank should help shed some light on this new and exciting area, and could be useful to professionals in the field of data mining, image processing and adaptive systems, or anyone else who may be considering applying neural networks for knowledge extraction e.g. in marketing.Books on Demand GmbH, Überseering 33, 22297 Hamburg 176 pp. Englisch.

Bestandsnummer des Verkäufers 9783844329414

Bibliografische Details

• Titel: Knowledge Extraction with Neural Networks
• Verlag: LAP LAMBERT Academic Publishing Okt 2011
• Erscheinungsjahr: 2011
• Sprache: Englisch
• ISBN-10: 3844329412
• ISBN-13: 9783844329414
• Einband: Taschenbuch
• Zustand: Neu
• Abmessungen: 220B x 150 H x 12 T Millimeter Breite: 220 mm, Höhe: 150 mm, Tiefe: 12 mm
• Gewicht: 280 Gramm

Über diesen Titel

Inhaltsangabe

Recent turbulences of global economy impose strong requirements on efficiency, flexibility, and reliability of new products and services. Unfortunately, for most techniques applicable to the design of complex adaptive systems – artificial neural networks, fuzzy logic, cluster analysis, etc. – it is still complicated to interpret what they are actually doing – especially when processing large sets of high-dimensional data. Yet understanding and correct interpretation of the knowledge extracted by the applied model represent decisive issues for the ability to detect significant, e.g. novel input patterns, to identify their characteristic features and to assess their future development. This book provides new means to handle these problems with artificial neural networks of the Back-Propagation type. Two case studies involving image classification and analysis of economical data provided by the World Bank should help shed some light on this new and exciting area, and could be useful to professionals in the field of data mining, image processing and adaptive systems, or anyone else who may be considering applying neural networks for knowledge extraction e.g. in marketing.