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 57.
... with reasonably large numbers of measurements (i.e. variables) made on each entity in one or more samples simultaneously (Dillon and Goldstein, 1984).
Example 1: Sn-Ge-Cd-Cu-Fe-bearing samples from Barquilla deposit in Spain................... 216 6.8.3. Example 2: Chromitite ores from the Bushveld Igneous ...
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 ...
When all the network weights are adjusted for the k'th exemplar (i.e. for all i and j) as indicated above, it is referred to as per sample training or ...
Sampling: Draw a samplex from the input distribution with a certain probability. ii. Similarity matching: Find the winning neuron I(x) at time t, ...
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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