Factor Sensitivity Analysis with Neural Network Simulation based on Perturbation System

Perturbation system is often used in the factor sensitivity analysis with neural network design. The two major and key problems: the sensitivity definition and the input perturbation ratio are investigated in this study. Besides, four models of sensitivity analysis are considered in the investigation. Through comparison and analysis, results show that the definition of sensitivity derived from the partial derivatives is relatively more rational than others and, the optimum range of the input perturbation ratio could be [-20%, 20%] for a general case. Additionally, the effect of quality of model on the prediction accuracy of the sensitivity is discussed in this paper, and their correlation is revealed.