Prediction of immeasurable variables using artificial neural networks
One of the significant problems in process industry is real-time determination of laboratory values. Laboratory analysis is usually done periodically and can take significant amount time. The information about values between two laboratory analyses doesn't exist. Very often in that time big cha...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
National Society of Processing and Energy in Agriculture, Novi Sad
2011-01-01
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| Series: | Journal on Processing and Energy in Agriculture |
| Subjects: | |
| Online Access: | https://scindeks-clanci.ceon.rs/data/pdf/1821-4487/2011/1821-44871104260P.pdf |
| _version_ | 1811210911729319936 |
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| author | Popov Nikola Stanišić Darko Jorgovanović Nikola Damljanović Dejan |
| author_facet | Popov Nikola Stanišić Darko Jorgovanović Nikola Damljanović Dejan |
| author_sort | Popov Nikola |
| collection | DOAJ |
| description | One of the significant problems in process industry is real-time determination of laboratory values. Laboratory analysis is usually done periodically and can take significant amount time. The information about values between two laboratory analyses doesn't exist. Very often in that time big change happens and it is detected too late. Because of that it becomes necessary to undertake radical corrective actions to steer the process to desired performance. Our goal was to develop prediction system which would be able to calculate and predict laboratory values in the real time. In this paper system for real time prediction of Free Calcium Oxide contained in clinker is presented. This is one of the parameters which determine the quality of clinker, which is used in cement production. For prediction, artificial neural networks were used and findings are presented in this paper. The same approach can be used in development of similar prediction systems for real time prediction of laboratory measurements in agricultural industry, process industry, chemical industry …. |
| first_indexed | 2024-04-12T05:03:59Z |
| format | Article |
| id | doaj.art-aba2fb7d01a141279f4cf66054dce314 |
| institution | Directory Open Access Journal |
| issn | 1821-4487 2956-0195 |
| language | English |
| last_indexed | 2024-04-12T05:03:59Z |
| publishDate | 2011-01-01 |
| publisher | National Society of Processing and Energy in Agriculture, Novi Sad |
| record_format | Article |
| series | Journal on Processing and Energy in Agriculture |
| spelling | doaj.art-aba2fb7d01a141279f4cf66054dce3142022-12-22T03:46:55ZengNational Society of Processing and Energy in Agriculture, Novi SadJournal on Processing and Energy in Agriculture1821-44872956-01952011-01-011542602621821-44871104260PPrediction of immeasurable variables using artificial neural networksPopov Nikola0Stanišić Darko1Jorgovanović Nikola2Damljanović Dejan3Faculty of Technical Sciences, Novi Sad, SerbiaFaculty of Technical Sciences, Novi Sad, SerbiaFaculty of Technical Sciences, Novi Sad, SerbiaLafarge BFC, Beočin, SerbiaOne of the significant problems in process industry is real-time determination of laboratory values. Laboratory analysis is usually done periodically and can take significant amount time. The information about values between two laboratory analyses doesn't exist. Very often in that time big change happens and it is detected too late. Because of that it becomes necessary to undertake radical corrective actions to steer the process to desired performance. Our goal was to develop prediction system which would be able to calculate and predict laboratory values in the real time. In this paper system for real time prediction of Free Calcium Oxide contained in clinker is presented. This is one of the parameters which determine the quality of clinker, which is used in cement production. For prediction, artificial neural networks were used and findings are presented in this paper. The same approach can be used in development of similar prediction systems for real time prediction of laboratory measurements in agricultural industry, process industry, chemical industry ….https://scindeks-clanci.ceon.rs/data/pdf/1821-4487/2011/1821-44871104260P.pdfneural networkmodel developmentfree calcium oxideopc client |
| spellingShingle | Popov Nikola Stanišić Darko Jorgovanović Nikola Damljanović Dejan Prediction of immeasurable variables using artificial neural networks Journal on Processing and Energy in Agriculture neural network model development free calcium oxide opc client |
| title | Prediction of immeasurable variables using artificial neural networks |
| title_full | Prediction of immeasurable variables using artificial neural networks |
| title_fullStr | Prediction of immeasurable variables using artificial neural networks |
| title_full_unstemmed | Prediction of immeasurable variables using artificial neural networks |
| title_short | Prediction of immeasurable variables using artificial neural networks |
| title_sort | prediction of immeasurable variables using artificial neural networks |
| topic | neural network model development free calcium oxide opc client |
| url | https://scindeks-clanci.ceon.rs/data/pdf/1821-4487/2011/1821-44871104260P.pdf |
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