  The systems monitoring the location of public transport vehicles rely on
wireless transmission. The location readings from GPS-based devices are
received with some latency caused by periodical data transmission and temporal
problems preventing data transmission. This negatively affects identification
of delayed vehicles. The primary objective of the work is to propose short term
hybrid delay prediction method. The method relies on adaptive selection of
Hoeffding trees, being stream classification technique and multilayer
perceptrons. In this way, the hybrid method proposed in this study provides
anytime predictions and eliminates the need to collect extensive training data
before any predictions can be made. Moreover, the use of neural networks
increases the accuracy of the predictions compared with the use of Hoeffding
trees only.
