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 59.
There is no reason why other methods cannot also be simulated or executed in a similar way (and are indeed). Since the book is aimed at the practicing ...
... chemical sample (Krzanowski and Marriot, 1994). In these cases the number of variables usually exceed the number of samples by far. Similar problems ...
These processing nodes are usually divided into disjoint subsets or layers, in which all the nodes have similar computational characteristics.
Zm] The potential for a particular node in this single layer feedforward neural network is similar to that for the neuron model, except that a double index ...
Similar to Hebbian learning, the initial weight vector should also be zero. 1.5.2. Unsupervised training a) Hebbian and anti-Hebbian learning rule For the ...
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