FITTING FUNCTIONS AND THEIR DERIVATIVES WITH NEURAL NETWORKS By
A. Pukrittayakamee · SHAREOK (University of Oklahoma; Oklahoma State University; Central Oklahoma University) · 2009
Scope and Method of Study: The objective of this work was to study methods of simultaneously approximating functions and their first-order derivatives using multilayer feedforward neural networks. There are a few methods proposed today to simultaneously approximate both functions and their first derivatives, but they require modifications to the network structure. The new method works with any multilayer feedfoward neural network, by forming a new performance index that combines both the function error and the first derivative error. We tested and analyzed the results of the proposed method on both analytic and real-world problems.