Predictive study of ultra-low emissions from dual-fuel engine using Artificial Neural Networks combined with Genetic algorithm
10.1080/15435075.2019.1650048
Saved in:
Main Authors: | Wenbin Yu, Feiyang Zhao |
---|---|
Other Authors: | MECHANICAL ENGINEERING |
Format: | Article |
Published: |
Taylor & Francis
2019
|
Online Access: | https://scholarbank.nus.edu.sg/handle/10635/158393 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | National University of Singapore |
Similar Items
-
Prediction of critical properties of biodiesel fuels from FAMEs compositions using intelligent genetic algorithm based back propagation neural network
by: Wenbin Yu, et al.
Published: (2021) -
Gains self-tuning of a large compliance system by combining artificial neural networks and genetic algorithms
by: Yuan, Yuan.
Published: (2009) -
Particulate emissions from a stationary engine fueled with ultra-low-sulfur diesel and waste-cooking-oil-derived biodiesel
by: Betha, R., et al.
Published: (2014) -
Particulate emissions from a stationary engine fueled with ultra-low-sulfur diesel and waste-cooking-oil-derived biodiesel
by: Betha, R., et al.
Published: (2014) -
A dual layered PSO algorithm for evolving an Artificial Neural Network controller
by: Subramanyam, V., et al.
Published: (2014)