Open Access
| Issue |
E3S Web Conf.
Volume 461, 2023
Rudenko International Conference “Methodological Problems in Reliability Study of Large Energy Systems“ (RSES 2023)
|
|
|---|---|---|
| Article Number | 01063 | |
| Number of page(s) | 4 | |
| DOI | https://doi.org/10.1051/e3sconf/202346101063 | |
| Published online | 12 December 2023 | |
- Ismail, S. A., Chen, G., Baillie, C., and Symes, T. (2011). Energy uses for cotton ginning in Australia. Biosystems Engineering, 109(2), 140–147. https://doi.org/10.1016/j.biosystemseng.2011.02.010. [CrossRef] [Google Scholar]
- Dube K. J., Ingale L. T., and Ingle S. T. (2013). Respiratory Impairment in Cotton-Ginning Workers Exposed to Cotton Dust. International Journal of Occupational Safety and Ergonomics, 19(4), 551–560. https://doi.org/10.1080/10803548.2013.11077009 [CrossRef] [PubMed] [Google Scholar]
- Sahu S., and Pramanik K. (2015). Delignification of cotton gin waste and its optimization by using white rot fungus Pycnoporus cinnabarinus. Journal of Environmental Biology, 36(3), 661. [Google Scholar]
- Shanbeh M., Hasani H., and Tabatabaei S. A. (2011). Modelling and predicting the breaking strength and mass irregularity of cotton rotor-spun yarns containing cotton fiber recovered from ginning process by using artificial neural network algorithm. Modelling and Simulation in Engineering, 2011, 1-8. [CrossRef] [Google Scholar]
- Fue K. G., Porter W. M., Barnes E. M., and Rains, G. C. (2020). An extensive review of mobile agricultural robotics for field operations: focus on cotton harvesting. AgriEngineering, 2(1). [Google Scholar]
- Hardin I.V, Barnes R. G., Delhom E. M., Wanjura C. D., and Ward J. K. (2022). Internet of things: Cotton harvesting and processing. Computers and Electronics in Agriculture, 202, 107294 [CrossRef] [Google Scholar]
- Muratov Kh., Ishnazarov O., Isakov A., and Nuritov I. (2023) Assessment of effect of lining material on energy efficiency of starting up ball mills. E3S Web of Conferences, 365, 04005. DOI: https://doi.org/10.1051/e3sconf/202336504005 [CrossRef] [EDP Sciences] [Google Scholar]
- Khushiev S., Ishnazarov O., Juraev S., Izzatillaev J., and Karakulov A. Construction of an electric drive system for borehole pumps with frequency control. AIP Conference Proceedings 5 December 2022; 2686 (1): 020018. https://doi.org/10.1063/5.0114016 [Google Scholar]
- Sariev E., and Germano G. (2020) Bayesian regularized artificial neural networks for the estimation of the probability of default. Quantitative Finance, 20(2), 311-328, DOI: 10.1080/14697688.2019.1633014 [CrossRef] [Google Scholar]
- Neal R. Bayesian learning for neural networks (1996). PhD Thesis, University of Toronto, Toronto, Canada [Google Scholar]
- Sariev E. and Germano G. (2019) An innovative feature selection method for support vector machines and its test on the estimation of thecredit risk of default. Rev. Financ. Econ., 37, 404–427. [CrossRef] [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.