Predicting the recovery and nonrecoverable compliance behaviour of asphalt binders using artificial neural networks

HIGHLIGHTS

  • who: Abdulrahman Hamid and collaborators from the Department of Civil and Environmental Engineering, University of Waterloo, Waterloo, ON N L , Canada have published the research: Predicting the Recovery and Nonrecoverable Compliance Behaviour of Asphalt Binders Using Artificial Neural Networks, in the : Processes 2022, 10, 2633. of /2022/
  • what: The aim of this research was to use Artificial Neural Networks (ANNs) to predict the (R) and compliance (Jnr ) behaviour of asphalt binder based on mechanical test parameters and rheological properties of asphalt binder. The aim of this method is to iteratively modify the weights in the . . .

     

    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 ?