Predicting Density, Viscosity,Volume and Temperature for Kerosene and Gas Oil Suplied by Doura Refinery From a Measured Experimental Result as Input Variables to Artificial Neural Network (ANN)

Abstract: This study shows the possibility of predicting specific characteristicsof kerosene and gas oil using experimental measurements as inputs. Variables for programming (ANN) of artificial neuron networks. This study examines fuels from Dora refinery and investigates the relationship between fu...

Full description

Saved in:
Bibliographic Details
Main Author: Dr.Kafaa F.Abbas Alani
Format: Article
Language:English
Published: University of Misan College of Engineering 2025-06-01
Series:Misan Journal of Engineering Sciences
Online Access:https://uomisan.edu.iq/eng/mjes/index.php/eng/article/view/134
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1850103101004972032
author Dr.Kafaa F.Abbas Alani
author_facet Dr.Kafaa F.Abbas Alani
author_sort Dr.Kafaa F.Abbas Alani
collection DOAJ
description Abstract: This study shows the possibility of predicting specific characteristicsof kerosene and gas oil using experimental measurements as inputs. Variables for programming (ANN) of artificial neuron networks. This study examines fuels from Dora refinery and investigates the relationship between fuel density and various properties such as volume, viscosity, and temperature. The correlation equation was determined by several linear regression analyses, and the coefficient (R2) showed some measurements in a strong achieved:R = 0.99986 for keosene, R= 0.99886 for gas oil.
format Article
id doaj-art-aa5bd662c4b641b8acb31f8efb3527c3
institution DOAJ
issn 2957-4242
2957-4250
language English
publishDate 2025-06-01
publisher University of Misan College of Engineering
record_format Article
series Misan Journal of Engineering Sciences
spelling doaj-art-aa5bd662c4b641b8acb31f8efb3527c32025-08-20T02:39:37ZengUniversity of Misan College of EngineeringMisan Journal of Engineering Sciences2957-42422957-42502025-06-014125026210.61263/mjes.v4i1.134134Predicting Density, Viscosity,Volume and Temperature for Kerosene and Gas Oil Suplied by Doura Refinery From a Measured Experimental Result as Input Variables to Artificial Neural Network (ANN)Dr.Kafaa F.Abbas Alani0Al Farabi University ColllegeAbstract: This study shows the possibility of predicting specific characteristicsof kerosene and gas oil using experimental measurements as inputs. Variables for programming (ANN) of artificial neuron networks. This study examines fuels from Dora refinery and investigates the relationship between fuel density and various properties such as volume, viscosity, and temperature. The correlation equation was determined by several linear regression analyses, and the coefficient (R2) showed some measurements in a strong achieved:R = 0.99986 for keosene, R= 0.99886 for gas oil.https://uomisan.edu.iq/eng/mjes/index.php/eng/article/view/134
spellingShingle Dr.Kafaa F.Abbas Alani
Predicting Density, Viscosity,Volume and Temperature for Kerosene and Gas Oil Suplied by Doura Refinery From a Measured Experimental Result as Input Variables to Artificial Neural Network (ANN)
Misan Journal of Engineering Sciences
title Predicting Density, Viscosity,Volume and Temperature for Kerosene and Gas Oil Suplied by Doura Refinery From a Measured Experimental Result as Input Variables to Artificial Neural Network (ANN)
title_full Predicting Density, Viscosity,Volume and Temperature for Kerosene and Gas Oil Suplied by Doura Refinery From a Measured Experimental Result as Input Variables to Artificial Neural Network (ANN)
title_fullStr Predicting Density, Viscosity,Volume and Temperature for Kerosene and Gas Oil Suplied by Doura Refinery From a Measured Experimental Result as Input Variables to Artificial Neural Network (ANN)
title_full_unstemmed Predicting Density, Viscosity,Volume and Temperature for Kerosene and Gas Oil Suplied by Doura Refinery From a Measured Experimental Result as Input Variables to Artificial Neural Network (ANN)
title_short Predicting Density, Viscosity,Volume and Temperature for Kerosene and Gas Oil Suplied by Doura Refinery From a Measured Experimental Result as Input Variables to Artificial Neural Network (ANN)
title_sort predicting density viscosity volume and temperature for kerosene and gas oil suplied by doura refinery from a measured experimental result as input variables to artificial neural network ann
url https://uomisan.edu.iq/eng/mjes/index.php/eng/article/view/134
work_keys_str_mv AT drkafaafabbasalani predictingdensityviscosityvolumeandtemperatureforkeroseneandgasoilsupliedbydourarefineryfromameasuredexperimentalresultasinputvariablestoartificialneuralnetworkann