A Study on Extreme Learning Machine for Gasoline Engine Torque Prediction

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 accu...

Full description

Bibliographic Details
Main Authors: Weiying Zeng, Mohammed A. S. Khalid, Xiaoye Han, Jimi Tjong
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Artificial neural network
extreme learning machine
gasoline engine model
torque prediction
weight factor
Online Access:https://ieeexplore.ieee.org/document/9108209/

Internet

https://ieeexplore.ieee.org/document/9108209/

Similar Items