Sorry for my late response.

The network is commonly referred to as Backpropagation Network. The network has one input layer, one middle layer, and one output layer. Each layer contains a bunch of neural nodes or processing units. Nodes in input layer are connected to those in middle layer (or hidden layer) and nodes in hidden layer are connected to those in output layer.

Backpropagation in network’s name refers to the process of training weights of the network. After training is complete (there are many ways to define completion), network feeds input forward (input → hidden → output layer) to make a prediction at the output layer.

Let me know if you need further information.