<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>The paper presents the main methods of energy optimization of the purification processes, by implementing computer-based technologies. Both the process control possibilities using fuzzy logic, for situations where the process model is not very certain, but it must be well known, as well as the use of feed-forward artificial neural networks trained by the back-propagation method using the learning mechanism are reviewed and supervised (using the Matlab program).</p>
</abstract>

The paper presents the main methods of energy optimization of the purification processes, by implementing computer-based technologies. Both the process control possibilities using fuzzy logic, for situations where the process model is not very certain, but it must be well known, as well as the use of feed-forward artificial neural networks trained by the back-propagation method using the learning mechanism are reviewed and supervised (using the Matlab program).

Energy Optimization of Wastewater Cleaning Technologies

University of Oradea, Faculty of Construction

Cadastre and Architecture, Department of Constructions

Journal of Applied Engineering Sciences

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

{"article-title":"Energy Optimization of Wastewater Cleaning Technologies"}

The paper presents the main methods of energy optimization of the purification processes, by implementing computer-based technologies. Both the process control...

Energy Optimization of Wastewater Cleaning Technologies

Online veröffentlicht: 21. Dez. 2022

Seitenbereich: 173 - 178

Eingereicht: 30. Aug. 2022

Akzeptiert: 10. Sept. 2022

DOI: https://doi.org/10.2478/jaes-2022-0023

Schlüsselwörter
residential sector, buildings, energy efficiency

© 2022 G.L. Ionescu et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Energy Optimization of Wastewater Cleaning Technologies

Online veröffentlicht: 21. Dez. 2022

Seitenbereich: 173 - 178

Eingereicht: 30. Aug. 2022

Akzeptiert: 10. Sept. 2022

DOI: https://doi.org/10.2478/jaes-2022-0023

Schlüsselwörterresidential sector, buildings, energy efficiency

© 2022 G.L. Ionescu et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Schlüsselwörter
residential sector, buildings, energy efficiency