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  • 标题:The use of artificial neural networks for analyzing the sensitivity of a retention tank
  • 本地全文:下载
  • 作者:Kamil Pochwat
  • 期刊名称:E3S Web of Conferences
  • 印刷版ISSN:2267-1242
  • 电子版ISSN:2267-1242
  • 出版年度:2018
  • 卷号:45
  • 页码:1-8
  • DOI:10.1051/e3sconf/20184500066
  • 出版社:EDP Sciences
  • 摘要:Designing retention facilities is a complex engineering process that requires the collection of the detailed hydrological data of a catchment and hydraulic sewerage system. The acquired data are necessary to prepare a model of the retention tank in appropriate software for hydrodynamic modelling. The article shows the results of tests concerning the analysis of the sensitivity of a sewerage model of a rainwater retention tank which may be implemented in this software. The results of tests allowed determining the impact of the individual hydraulic characteristics of the catchment and the sewerage system on the required retention capacity of a tank. A planned analysis is performed based on artificial neural networks and the required data are acquired by hydrodynamic simulations in SWMM 5.1.
  • 其他摘要:Designing retention facilities is a complex engineering process that requires the collection of the detailed hydrological data of a catchment and hydraulic sewerage system. The acquired data are necessary to prepare a model of the retention tank in appropriate software for hydrodynamic modelling. The article shows the results of tests concerning the analysis of the sensitivity of a sewerage model of a rainwater retention tank which may be implemented in this software. The results of tests allowed determining the impact of the individual hydraulic characteristics of the catchment and the sewerage system on the required retention capacity of a tank. A planned analysis is performed based on artificial neural networks and the required data are acquired by hydrodynamic simulations in SWMM 5.1.
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