A Study on Extreme Learning Machine for Gasoline Engine Torque Prediction

This research presents an extreme learning machine (ELM) based neural network modeling technique for gasoline engine torque prediction. The technique adopts a single-hidden layer feedforward neural network (SLFN) structure which has the potential to approximate any continuous function with high accuracy. To verify the robustness of this technique, over 3300 data points collected from a real-world gasoline engine are used to train, validate, and …