GCN is a neural network comprising layers that perform convolution operations defined over a graph data. Convolution cannot be simply applied to graphs, unlike images or series in which the relationship between neighboring elements is not fixed. There are two types of convolutions on graphs: one dealing with signals over graphs and the other based on the spatial structure of graphs. Here, we describe graph convolution defined on the space used in this study. The output of the l layer of node i depends only on its neighbors, and is defined as follows: 42