Artificial Neural Networks (ANNs)

• 19 different neural network architectures are applied.
• The networks differed from each other in the number of hidden layers and in the number of neurons in a hidden layer.
• Every node in a layer (input, hidden and output) in these feed-forward networks (multilayer preceptors) is fully connected (by adjustable weights) to every node in a subsequent layer.
• Thus, the total input to a node of the hidden layer can be written as follows:
  
  
  
• W are the adjustable connection weights.
• Constant terms, so called biases are given by introducing an extra input to each unit.
• Transfer functions are of the logsig type, thus a unit has a real-valued output: