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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.
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Submitted on : Tuesday, September 24, 2019 - 9:57:04 AM
Last modification on : Monday, March 29, 2021 - 11:50:04 AM
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Ivan Pisa, Ramon Vilanova, Ignacio Santín, Jose 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⟩

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