Exploratory analysis of metallurgical process data with neural networks and related methods / C. Aldrich
- Aldrich, C. (Chris)
- Amsterdam ; Boston ; London : Elsevier, 2002.
- 1st ed.
- Physical Description:
- xvi, 370 p. : ill. ; 25 cm. + 1 computer optical disc (4 3/4 in.)
- INTRODUCTION TO NEURAL NETWORKS: Artificial neural networks from an engineering perpective -- Brief history of neural networks -- Structures of neural networks -- Training rules -- Neural network models -- Neural networks and statistical models -- Applications in the process industries -- TRAINING OF NEURAL NETWORKS: Gradient descent methods -- Conjugate gradients -- Newtons method and quasi newton method -- Levenberg marguardt algorithm -- Stochastic methods -- Regularization and pruning of neural network models -- Pruning algorithms for neural networks -- Constructive algorithms for neural networks -- LATENT VARIABLE METHODS: Basics of latent structure analysis -- Principal component analysis -- Nonlinear approaches to latent variable extraction -- Principal component analysis with neural networks -- Feature extraction from digitised images of industrial flotation froths with autoassociative neural networks -- Alternative approaches to nonlinear principal component analysis -- Low dimensional reconstruction of data with nonlinear principal component methods -- Partial least squares pls models -- Multivariate statistical process control -- REGRESSION MODELS: Theoretical background to model development -- Regression and correlation -- Multicollinearity -- Outliers and influential observations -- Robust regression models -- Dummy variable regression -- Ridge regression -- Continuum regression -- Calibration of an on-line diagnostic monitoring system for comminution in a laboratory-scale ball mill -- Nonlinear regrssion models -- Modelling of a simple bimodal function -- Nonlinear modelling of consumption of an additive in a gold leach plant -- TOPOGRAPHICAL MAPPINGS WITH NEURAL NETWORKS: Objective functions for topographic maps -- Multidimensional scaling -- Sammon projections -- Artificially generated and benchmark data sets -- Visualization of flotation data from a base metal flotation plant -- Monitoring of a froth flotation plant -- Analysis of the liberation of gold with multidimensionally scaled maps -- Monitoring of metallurgical furnaces by use of topographic process maps -- and CLUSTER ANALYSIS: Similarity measures -- Grouping of data -- Hierarchical cluster analysis -- Optimal partitioning k means clustering -- Simple examples of hierarchical and k-means cluster analysis -- Clustering of large data sets -- Application of cluster analysis in process engineering -- Cluster analysis with neural networks -- EXTRACTION OF RULES FROM DATA WITH NEURAL NETWORKS: Neurofuzzy modeling of chemical process systems with ellipsoidal radial basis function neural networks and genetic algorithms -- Extraction of rules with the artificial neural network decision tree ann dt algorithm -- Combinatorial rule assembler cora algorithm -- INTRODUCTION TO THE MODELLING OF DYNAMIC SYSTEMS: Delay coordinates -- Lag or delay time -- Embedding dimension -- Characterization of attractors -- Detection of nonlinearities -- Singular spectrum analysis -- Recursive prediction -- DYNAMIC SYSTEMS ANALYSIS AND MODELLING: Effect of noise on periodic time series -- Autocatalysis in a continuous stirred tank reactor -- Effect of measurement and dynamic noise on the identification of an autocatalytic process -- Identification of an industrial platinum flotation plant by use of singular spectrum analysis and delay coordinates -- Identification of a hydrometallurgical process circuit -- EMBEDDING OF MULTIVARIATE DYNAMIC PROCESS SYSTEMS: Embedding of multivariate observations -- Multidimensional embedding methodology -- Application of the embedding method -- Modelling of NOx formation -- FROM EXPLORATORY DATA ANALYSIS TO DECISION SUPPORT AND PROCESS CONTROL: Anatomy of a knowledge based system -- Development of a decision support system for the diagnosis of corrosion problems -- Advanced process control with neural networks -- Symbiotic adaptive neuro evolution sana -- Neurocontrol of a ball mill grinding circuit -- Neurocontroller development and performance.
- Bibliography Note:
- Includes bibliographical references (p. 333-365) and index.
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