Soft Computing in Measurement and Information Acquisition

ISBN 10: 3540002464 / ISBN 13: 9783540002468

Published by Springer, 2003

About this Item

pp. 304 52:B&W 6.14 x 9.21in or 234 x 156mm (Royal 8vo) Case Laminate on White w/Gloss Lam.

Seller Inventory # 11290515

Bibliographic Details

• Title: Soft Computing in Measurement and Information Acquisition
• Publisher: Springer
• Publication Date: 2003
• Language: English
• ISBN 10: 3540002464
• ISBN 13: 9783540002468
• Binding: Hardcover
• Condition: New

About this title

Synopsis

This volume covers the fields of measurement and information acqulSltlon. It contains a collection of papers representing the current research trends in these areas. What are those trends? The first one is the enormous growth in the amount of information and the amazing technologies, which make this information available anywhere and anytime. The second one is a substantial development of methods of the information presentation including, to name just a few, multimedia, virtual environment, computer animation. The third one is the all-time boosting demand for improving the quality of decisions made on the base of this information in various applications ranging from engineering to business. Nowadays information acquisition should not only provide more information but also provide it in such a way as to assure effective and efficient processing of this information. And here comes a relatively new methodology of soft computing. Application of soft computing in measurement and information acquisition is considered in this volume.

From the Back Cover

The vigorous development of the internet and other information technologies have significantly expanded the amount and variety of sources of information available on decision making. This book presents the current trends of soft computing applications to the fields of measurements and information acquisition. Main topics are the production and presentation of information including multimedia, virtual environment, and computer animation as well as the improvement of decisions made on the basis of this information in various applications ranging from engineering to business. In order to make high-quality decisions, one has to fuse information of different kinds from a variety of sources with differing degrees of reliability and uncertainty. The necessity to use intelligent methodologies in the analysis of such systems is demonstrated as well as the inspiring relation of computational intelligence to its natural counterpart. This book includes several contributions demonstrating a further movement towards the interdisciplinary collaboration of the biological and computer sciences with examples from biology and robotics.