Artificial intelligence based gene expression programming (GEP) model prediction of Diesel engine performances and exhaust emissions under Diesosenol fuel strategies-Reference-Cited by-同舟云学术

Artificial intelligence based gene expression programming (GEP) model prediction of Diesel engine performances and exhaust emissions under Diesosenol fuel strategies

Published:2019-01 Issue: Volume:235 Page:317-325
ISSN:0016-2361
Container-title:Fuel
language:en
Short-container-title:Fuel

Author:

Bhowmik Subrata,Paul Abhishek,Panua Rajsekhar^ORCID,Ghosh Subrata Kumar^ORCID,Debroy Durbadal

Publisher

Elsevier BV

Subject

Organic Chemistry,Energy Engineering and Power Technology,Fuel Technology,General Chemical Engineering

Reference25 articles.

1. Artificial Neural Network Prediction of Diesel engine performance and emission fueled with Diesel-kerosene-ethanol blends: a fuzzy based optimization;Bhowmik;J Energy Res Technol,2017

2. A comparative study of Artificial Intelligence based models to predict performance and emission characteristics of a single cylinder Diesel engine fueled with Diesosenol;Bhowmik;J Therm Sci Eng Appl,201710

3. An experimental study of the performance, combustion and emission characteristics of a CI engine under dual fuel mode using CNG and oxygenated pilot fuel blends;Paul;Energy,2015

4. Estimation of petrol and diesel adulteration with kerosene and assessment of usefulness of selected automobile fuel quality test parameters;Yadav;Int J Environ Sci Technol,2015

5. Diesoline, diesohol, and diesosene fuelled HCCI engine development;Singh;J Energy Resour Technol,2016

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