Rule extraction from neural networks by interval propagation
Vasile Palade, Daniel C. Neagu, G. Puscasu · 2002
This paper proposes a method of rule extraction from ordinary backpropagation neural networks, which do not have a structure that facilitates rule extraction. This method is based on interval propagation across the network. The method of rule extraction uses a procedure for inverting a neural network, which is also presented. A common benchmark control problem was used to test the rule extraction and inversion methods.