Exploratory Analysis of Metallurgical Process Data with Neural Networks and Related Methods
Elsevier, 2002. gada 19. apr. - 386 lappuses
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.
1.5. rezultāts no 50.
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The data are obtained by exposing a chemical sample to an energy source, and recording the resulting absorbance as a continuous trace over a range of ...
Items of knowledge are furthermore distributed across the network and reasonable responses are obtained when the network is presented with incomplete, ...
... d) Correlation learning rule The correlation rule is obtained by substituting r = di in the general learning rule (equation 1.12), so that Awi = Bd;x, ...
... for a given matrix of parameters W, is obtained by integration over the x space (P), that is row b-sists, wood, (1.40) For a given data set of size n, ...
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CHAPTER 3 LATENT VARIABLE METHODS
CHAPTER 4 REGRESSION MODELS
CHAPTER 5 TOPOGRAPHICAL MAPPINGS WITH NEURAL NETWORKS
CHAPTER 6 CLUSTER ANALYSIS
CHAPTER 7 EXTRACTION OF RULES FROM DATA WITH NEURAL NETWORKS
CHAPTER 8 INTRODUCTION TO THE MODELLING OF DYNAMIC SYSTEMSCHAPTER
DYNAMIC SYSTEMS ANALYSIS AND MODELLING
CHAPTER 10 EMBEDDING OF MULTIVARIATE DYNAMIC PROCESS SYSTEMS
CHAPTER 11 FROM EXPLORATORY DATA ANALYSIS TO DECISION SUPPORT AND PROCESS CONTROL
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Exploratory Analysis of Metallurgical Process Data with Neural Networks and ...
Ierobežota priekšskatīšana - 2002