Exploratory Analysis of Metallurgical Process Data with Neural Networks and Related Methods ( Volume 12 )

Publication series :Volume 12

Author: Aldrich   C.  

Publisher: Elsevier Science‎

Publication year: 2002

E-ISBN: 9780080531465

P-ISBN(Paperback): 9780444503121

P-ISBN(Hardback):  9780444503121

Subject: TF Metallurgical Industry;TP3 Computers

Language: ENG

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Description

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 of the field. Also, although the book focuses on neural networks, they cannot be divorced from their statistical framework and this is discussed in length. The book is therefore a blend of basic theory and some of the most recent advances in the practical application of neural networks.

Chapter

Front Cover

pp.:  1 – 4

Copyright Page

pp.:  5 – 6

Preface

pp.:  6 – 8

Table of Contents

pp.:  8 – 18

CHAPTER 2. TRAINING OF NEURAL NETWORKS

pp.:  67 – 91

CHAPTER 3. LATENT VARIABLE METHODS

pp.:  91 – 129

CHAPTER 4. REGRESSION MODELS

pp.:  129 – 189

CHAPTER 5. TOPOGRAPHICAL MAPPINGS WITH NEURAL NETWORKS

pp.:  189 – 216

CHAPTER 6. CLUSTER ANALYSIS

pp.:  216 – 245

CHAPTER 7. EXTRACTION OF RULES FROM DATA WITH NEURAL NETWORKS

pp.:  245 – 279

CHAPTER 8. INTRODUCTION TO THE MODELLING OF DYNAMIC SYSTEMSCHAPTER

pp.:  279 – 302

CHAPTER 9. CASE STUDIES: DYNAMIC SYSTEMS ANALYSIS AND MODELLING

pp.:  302 – 316

CHAPTER 10. EMBEDDING OF MULTIVARIATE DYNAMIC PROCESS SYSTEMS

pp.:  316 – 330

CHAPTER 11. FROM EXPLORATORY DATA ANALYSIS TO DECISION SUPPORT AND PROCESS CONTROL

pp.:  330 – 350

REFERENCES

pp.:  350 – 383

INDEX

pp.:  383 – 387

APPENDIX: DATA FILES

pp.:  387 – 388

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