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 64.
Statistics associated with principal component analysis models............................................... 77 3.2.3. Practical considerations regarding ...
The rule minimized the summed square error during training associated with the classification of patterns. The ADALINE network and its MADALINE (Multiple ...
An additional input can be defined for some neurons, i.e. x0, with associated weight w0. This input is referred to as a bias and has a fixed value of -1.
... as well as its neighbouring nodes (constituting the adaptation zone associated with the winning node) are subsequently adjusted in order to move the ...
The weights of the winning node, as well as its neighbouring nodes, which constitute the adaptation zone associated with the winning node are subsequently ...
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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