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...
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| Format: | Article |
| Language: | English |
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University of Misan College of Engineering
2025-06-01
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| Series: | Misan Journal of Engineering Sciences |
| Online Access: | https://uomisan.edu.iq/eng/mjes/index.php/eng/article/view/134 |
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| 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 |