Comparison of machine learning algorithms for predicting diesel/biodiesel/iso-pentanol blend engine performance and emissions-Reference-Cited by-同舟云学术

Comparison of machine learning algorithms for predicting diesel/biodiesel/iso-pentanol blend engine performance and emissions

Published:2023-11 Issue:11 Volume:9 Page:e21365
ISSN:2405-8440
Container-title:Heliyon
language:en
Short-container-title:Heliyon

Author:

Şahin Seda^ORCID

Publisher

Elsevier BV

Subject

Multidisciplinary

Reference62 articles.

1. Performance and emission prediction of a compression ignition engine fueled with biodiesel-diesel blends: a combined application of ANN and RSM based optimization;Aydın;Fuel,2020

2. Experimental investigation and prediction of performance and emission responses of a CI engine fuelled with different metal-oxide based nanoparticles–diesel blends using different machine learning algorithms;Ağbulut;Energy,2021

3. Evaluation of energetic-exergetic and sustainability parameters of biodiesel fuels produced from palm oil and opium poppy oil as alternative fuels in diesel engines;Şanli;Fuel,2019

4. Improvements to the composition of fusel oil and analysis of the effects of fusel oil–gasoline blends on a spark-ignited (SI) engine’s performance and emissions;Simsek;Energies,2018

5. Combustion and emission characteristics of isoamyl alcohol-gasoline blends in spark ignition engine;Uslu;Fuel,2020

Cited by 5 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Investigation of diesel-watermelon seed biodiesel-isoamyl alcohol blends in CI engine using Response Surface Methodology optimisation;Industrial Crops and Products;2024-10

2. Prediction of Oil–Water Two-Phase Flow Patterns Based on Bayesian Optimisation of the XGBoost Algorithm;Processes;2024-08-07

3. Emission and performance investigation of mango seed oil biodiesel supplied with n-pentanol and n-hexanol additives and optimization of fuel blends using modified deep neural network;International Journal of Chemical Reactor Engineering;2024-04-01

4. Comparative diesel engine performance and emission forecasting using extreme learning and quadratic regression techniques burning waste cooking biodiesel;International Journal of Hydrogen Energy;2024-03

5. A Comprehensive Review on Deep Learning Applications in Advancing Biodiesel Feedstock Selection and Production Processes;SSRN Electronic Journal;2024