A high-performance computing (HPC) based integrated multithreaded model predictive control (MPC) for water supply networks
Authors:
- Krzysztof Gaska,
- Agnieszka Generowicz,
- Izabela Zimoch,
- Józef Ciuła,
- Zsuzsanna Iwanicka
Abstract
The article presents the concept of an intelligent system of multithreaded, hierarchical predictive control of water supply and sewage networks using a parallel computational architecture. The predominant element of the proposed control system over other hitherto functioning systems is the element of predicting future events (MPC model). This feature, combined with the self-learning intelligent control system, not only allows you to react to changes in sensor state, but also anticipate these changes and adjust the system in advance to prepare for predicted situation, which is particularly important in systems with high iner- tia as extensive water supply and sewage networks. The technologically advanced solutions proposed by the authors, ie the HPC (High Performance Computing) ICT system, including the requesting module allows (by analyzing the space of states and events in real time) to predict future behaviors of individual elements of the system and effectively react to unknown cases, sup- porting the making of strategic decisions.
- Record ID
- CUTa8cac254008645869ccca5b04e6aa2e7
- Publication categories
- ;
- Author
- Journal series
- Architecture Civil Engineering Environment, ISSN 1899-0142, e-ISSN 2720-6947, Quarterly
- Issue year
- 2017
- Vol
- 10
- No
- 4
- Pages
- 141-151
- Other elements of collation
- rys.; Bibliografia (na s.) - 151; Bibliografia (liczba pozycji) - 19; Oznaczenie streszczenia - Abstr., Streszcz.; Numeracja w czasopiśmie - Vol. 10, No. 4
- Keywords in English
- Smart City, water distribution systems, sewerage systems, predictive models (MPC), artificial intelligence, GIS, parallel computing architecture (HPC)
- URL
- http://acee-journal.pl/1,7,Issues.html Opening in a new tab
- Language
- eng (en) English
- License
- Score (nominal)
- 11
- Publication indicators
- = 21
- Additional fields
- Indeksowana w: Web of Science
- Uniform Resource Identifier
- https://cris.pk.edu.pl/info/article/CUTa8cac254008645869ccca5b04e6aa2e7/
- URN
urn:pkr-prod:CUTa8cac254008645869ccca5b04e6aa2e7
* presented citation count is obtained through Internet information analysis, and it is close to the number calculated by the Publish or PerishOpening in a new tab system.