Neural network stochastic simulation applied for quantifying uncertainties

HIGHLIGHTS

  • who: tim from the PQJ X E Canada have published the paper: Neural network stochastic simulation applied for quantifying uncertainties, in the Journal: (JOURNAL)
  • what: The authors propose a simulation of properties based on supervised Neural network training at the existing drilling data set. This approach has been successfully tested for predicting the metal content of ore deposits . Discussion AND Conclusions This work proposes to use a stochastic simulation method based on training neural_networks.
  • how: The authors used a multi-layer perceptron (MLP) architecture with a feed-forward approach that is well adapted . . .

     

    Logo ScioWire Beta black

    If you want to have access to all the content you need to log in!

    Thanks :)

    If you don't have an account, you can create one here.

     

Scroll to Top

Add A Knowledge Base Question !

+ = Verify Human or Spambot ?