  We present a simple yet effective method for structure prediction of
two-dimensional structures. The method is based on a combination of neural
networks and evolutionary techniques. It allows finding pristine 2D structures
as well as structures grown on a substrate. Conducted tests show, that the
method is efficient and the calculations, based only on the information of
stoichiometry, can lead to stable structures. Since the algorithm is able to
address structures on a given substrate, it can be useful from the experimental
point of view.
