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 23.
... plants personnel have probably experienced a net loss in understanding of the complexities of the behaviour of the plant, owing to increased turnover,.
The trade-off between complexity and performance (number of nonseparable observations) is controlled by parameter C. The user has to select this parameter ...
The fitness of a neural network can be defined as required in terms of the error between target and actual outputs, as well as the complexity of the neural ...
The second term is the complexity penalty, which depends on the neural network model only. M. is referred to as a (complexity) regularization parameter, ...
The constant weight decay method (Ishikawa, 1996) is another simple approach with a complexity penalty term given by Ec(w) =X.jewiwi (2.33) For 1" order ...
Lietotāju komentāri - Rakstīt atsauksmi
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
Citi izdevumi - Skatīt visu
Exploratory Analysis of Metallurgical Process Data with Neural Networks and ...
Ierobežota priekšskatīšana - 2002