An Artificial Neural Network-based Real Time DSS to Manage the Discharges of a Wastewater Treatment Plant and Reduce the Flooding Risk-Reference-Cited by-同舟云学术

An Artificial Neural Network-based Real Time DSS to Manage the Discharges of a Wastewater Treatment Plant and Reduce the Flooding Risk

Published:2021 Issue: Volume: Page:
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Container-title:Proceedings of the 10th International Conference on Smart Cities and Green ICT Systems
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Author:

Termite Loris¹,Bonamente Emanuele²,Garinei Alberto³⁴,Bolpagni Daniele⁵,Menculini Lorenzo⁴,Marconi Marcello³⁴,Biondi Lorenzo³⁴,Chini Andrea⁶,Crespi Massimo⁶

Affiliation:

1. K-Digitale S.r.l., Perugia, Italy, --- Select a Country ---

2. Department of Engineering, University of Perugia, Perugia, Italy, --- Select a Country ---

3. Department of Sustainability Engineering, Guglielmo Marconi University, Rome, Italy, --- Select a Country ---

4. Idea-Re S.r.l., Perugia, Italy, --- Select a Country ---

5. A2A Ciclo Idrico S.p.A., Brescia, Italy, --- Select a Country ---

6. Radarmeteo S.r.l., Due Carrare (PD), Italy, --- Select a Country ---

Publisher

SCITEPRESS - Science and Technology Publications

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Intelligent sewage discharge control in a wastewater treatment plant during rainfall periods;Urban Water Journal;2023-02-14

2. A Decision Support System Based on Rainfall Nowcasting and Artificial Neural Networks to Mitigate Wastewater Treatment Plant Downstream Floods;Communications in Computer and Information Science;2022

3. The evaluation of wastewater treatment plant performance: a data mining approach;Journal of Engineering, Design and Technology;2021-10-28