  Predicting transit times of Coronal Mass Ejections (CMEs) from their initial
parameters is a very important subject, not only from the scientific
perspective, but also because CMEs represent a hazard for human technology. We
used a neural network to analyse transit times for 153 events with only two
input parameters: initial velocity of the CME, $v$, and Central Meridian
Distance, CMD, of its associated flare. We found that transit time dependence
on $v$ is showing a typical drag-like pattern in the solar wind. The results
show that the speed at which acceleration by drag changes to deceleration is
$v\approx$500 km s$^{-1}$. Transit times are also found to be shorter for CMEs
associated with flares on the western hemisphere than those originating on the
eastern side of the Sun. We attribute this difference to the eastward
deflection of CMEs on their path to 1 AU. The average error of the NN
prediction in comparison to observations is $\approx$12 hours which is
comparable to other studies on the same subject.
