Exploratory analysis of metallurgical process data with neural networks and related methods (eBook, 2002) [WorldCat.org]
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Exploratory analysis of metallurgical process data with neural networks and related methods

Author: C Aldrich
Publisher: Amsterdam ; Boston : Elsevier, 2002.
Series: Process metallurgy, 12.
Edition/Format:   eBook : Document : English : 1st edView all editions and formats
Summary:
This volume is concerned with the analysis and interpretation of multivariate measurements commonly found in the mineral and metallurgical industries, with the emphasis on the use of neural networks. The book is primarily aimed at the practicing metallurgist or process engineer, and a considerable part of it is of necessity devoted to the basic theory which is introduced as briefly as possible within the large scope  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Aldrich, C. (Chris).
Exploratory analysis of metallurgical process data with neural networks and related methods.
Amsterdam ; Boston : Elsevier, 2002
(DLC) 2002016356
(OCoLC)48777293
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: C Aldrich
ISBN: 9780444503121 0444503129 9780080531465 0080531466 1281019003 9781281019004
OCLC Number: 162130704
Description: 1 online resource (xvi, 370 pages) : illustrations
Contents: Introduction to neural networks --
Training of neural networks --
Latent variable methods --
Regression models --
Topographical mappings with neural networks --
Cluster analysis --
Extraction of rules from data with neural networks --
Introduction to the modelling of dynamic systemschapter --
Case studies: Dynamic systems analysis and modelling --
Embedding of multivariate dynamic process systems --
From exploratory data analysis to decision support and process control.
Series Title: Process metallurgy, 12.
Responsibility: C. Aldrich.
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Abstract:

Deals with analysis and interpretation of multivariate measurements commonly found in the mineral and metallurgical industries, with the emphasis on the use of neural networks. This book is aimed at  Read more...

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Henrik Saxen, Abo Akademi, Finland What our readers say about this title ...a welcome contribution to the field of exploratory data analysis. Henrik Saxen, Abo Akademi, Finland Derick Moolman, Read more...

 
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