Different variables affect the performance of the Stirling engine and are
considered in optimization and designing activities. Among these factors, torque and power
have the greatest effect on the robustness of the Stirling engine, so they need to be
determined with low uncertainty and high precision. In this article, the distribution of torque
and power are determined using experimental data. Specifically, a novel polynomial
approach is proposed to specify torque and power, on the basis of previous experimental
work. This research addresses the question of whether GMDH (group method of data
handling)-type neural networks can be utilized to predict the torque and power based on
determined parameters.
کلید واژگان :
GMDH; neural network; Stirling engine; torque; power
