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.

Includes bibliographical references (pages 333-365) and index.

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.

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