Automated System of Knowledge Base Acquisition for Lumber Drying Processes
| Parent link: | International Russian Automation Conference, RusAutoCon 2023: Proceedings, Sochi, October 10-16, 2023. P. 505-509.— .— Piscataway: IEEE, 2023 |
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| Περίληψη: | Title screen The paper deals with the problem of low-quality lumber drying at the initial operating stage of the drying chamber. Based on collected data of the drying process, the measured and calculated features of transient processes were identified. Their relation to the parameters and quality of drying is shown. A method collecting the features under consideration is proposed. The numerical evaluation of the features is associated with the result of drying. The implementation of the method for collecting the technological quality parameters relies on a web server for the formation of the drying process datasheet. The idea of implementing a neural network to confirm the assumption about the relation between the said features is considered. The neural network structure, which will probably allow to determine the degree of influence and relationship the features and the results of drying, is proposed. Текстовый файл AM_Agreement |
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2023
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| Διαθέσιμο Online: | https://doi.org/10.1109/RusAutoCon58002.2023.10272810 |
| Μορφή: | Ηλεκτρονική πηγή Κεφάλαιο βιβλίου |
| KOHA link: | https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=676097 |
| Περίληψη: | Title screen The paper deals with the problem of low-quality lumber drying at the initial operating stage of the drying chamber. Based on collected data of the drying process, the measured and calculated features of transient processes were identified. Their relation to the parameters and quality of drying is shown. A method collecting the features under consideration is proposed. The numerical evaluation of the features is associated with the result of drying. The implementation of the method for collecting the technological quality parameters relies on a web server for the formation of the drying process datasheet. The idea of implementing a neural network to confirm the assumption about the relation between the said features is considered. The neural network structure, which will probably allow to determine the degree of influence and relationship the features and the results of drying, is proposed. Текстовый файл AM_Agreement |
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| DOI: | 10.1109/RusAutoCon58002.2023.10272810 |