Predictive modeling and optimization of noise emissions in a palm oil methyl ester-fueled diesel engine using response surface methodology and artificial neural network integrated with genetic algorithm

Predictive modeling and optimization of noise emissions in a palm oil methyl ester-fueled diesel engine using response surface methodology and artificial neural network integrated with genetic algorithm

This research examines the predictive performance of two modeling techniques—Response Surface Methodology (RSM) and an Artificial Neural Network enhanced by a Genetic Algorithm (ANN-GA)—in relation to noise emission levels from a single-cylinder diesel engine running on palm oil methyl ester (POME)....

Full description

Bibliographic Details
Main Authors: Muhammad Zikri, Japri, Mohd Shahrir, Mohd Sani, Mohd Fadzil Faisae, Ab Rashid, Muriban, Jackly, Galang Sandy, Prayogo
Format: Article
Language:English
Published: Elsevier B.V. 2025
Subjects:
T Technology (General)
TA Engineering (General). Civil engineering (General)
TJ Mechanical engineering and machinery
TL Motor vehicles. Aeronautics. Astronautics
Online Access:http://umpir.ump.edu.my/id/eprint/43800/1/Predictive%20modeling%20and%20optimization%20of%20noise%20emissions%20in%20a%20palm%20oil%20methyl%20ester-fueled%20diesel.pdf

Internet

http://umpir.ump.edu.my/id/eprint/43800/1/Predictive%20modeling%20and%20optimization%20of%20noise%20emissions%20in%20a%20palm%20oil%20methyl%20ester-fueled%20diesel.pdf

Similar Items