Artificial Neural Networks Application to Support Plant Operation in the Wastewater Industry - Technological Innovation for Industry and Service Systems Access content directly
Conference Papers Year : 2019

Artificial Neural Networks Application to Support Plant Operation in the Wastewater Industry

Abstract

This communication presents the main aim, contextual and development framework of the PhD that is being conducted by the first author. In this PhD, main aim is the application of data driven methods to industrial processes in order to improve and support industrial operations. In this case, Wastewater Treatment Plants (WWTPs) are adopted as the industry where data driven methods will be applied. WWTPs are industries devoted to managing and process residual water coming from urban and industrial areas. Those type of industries apply highly-complex and nonlinear processes to reduce the contamination of water. Therefore, among the different data driven methods, in this PhD we will focus on the application of Artificial Neural Networks (ANNs) in order to improve and support the operations performed in this type of industries. ANNs are considered due to their ability in the modeling of highly-complex and nonlinear processes such as the WWTPs processes.
Fichier principal
Vignette du fichier
483289_1_En_22_Chapter.pdf (307.36 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-02295245 , version 1 (24-09-2019)

Licence

Attribution

Identifiers

Cite

Ivan Pisa, Ramon Vilanova, Ignacio Santín, Jose Lopez Vicario, Antoni Morell. Artificial Neural Networks Application to Support Plant Operation in the Wastewater Industry. 10th Doctoral Conference on Computing, Electrical and Industrial Systems (DoCEIS), May 2019, Costa de Caparica, Portugal. pp.257-265, ⟨10.1007/978-3-030-17771-3_22⟩. ⟨hal-02295245⟩
29 View
29 Download

Altmetric

Share

Gmail Facebook X LinkedIn More