In this paper a neural network approach is proposed to identify local PM10 (particulate matter with size smaller than 10 μm) precursor models based on the simulations of a multi-phase modelling system (GAMES).
Based on the simulations of MISBA and SAC-SMA for UBNB, La Niña and Indian Ocean Dipole (IOD) tend to have a wetting effect while El Niño has a drying effect on the streamflow of the UBNB.
The force time-series are produced based on the simulations of an array of the ballast particles in a wind-tunnel setup and it shows that the ballast flight is apt to happen as the rear part of the bogie cavity passing by the ballast bed.
Our performance evaluations are based on the simulations of 100 wireless mobile nodes that form a wireless ad hoc network over a rectangular (1000 × 1000 m) flat space.
Based on the simulations of nanoindentation at different loading speeds and indenter radii, it can be observed that the maximum load increased and the critical indentation depth decreased with the increase of loading speed.
One of our phylogenetic measures, PL, exclusively dependents on Blast to determine gene age and should be reliable based on the simulations of Alba and Castresana (2007).
