A Prescriptive Intelligent System for an Industrial Wastewater Treatment Process: Analyzing pH as a First Approach
| Autor: | Aymer Maturana, Carlos Cárdenas, G M Christian Quintero, Diego Gómez, Ricardo Mejía, Luis Arismendy |
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| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Scheme (programming language)
Industry 4.0 Computer science Process (engineering) lcsh:TJ807-830 Geography Planning and Development lcsh:Renewable energy sources 0211 other engineering and technologies 02 engineering and technology Management Monitoring Policy and Law artificial neural network (ANN) chemical oxygen demand (COD) data-driven decision making (DDDM) machine learning (ML) optimization wastewater treatment plant (WWTP) Profit (economics) Goods and services 0202 electrical engineering electronic engineering information engineering lcsh:Environmental sciences 021101 geological & geomatics engineering computer.programming_language lcsh:GE1-350 Artificial neural network Renewable Energy Sustainability and the Environment lcsh:Environmental effects of industries and plants Novelty Industrial engineering lcsh:TD194-195 Work (electrical) 020201 artificial intelligence & image processing computer |
| Zdroj: | Sustainability; Volume 13; Issue 8; Pages: 4311 Sustainability, Vol 13, Iss 4311, p 4311 (2021) |
| ISSN: | 2071-1050 |
| DOI: | 10.3390/su13084311 |
| Popis: | An important issue today for industries is optimizing their processes. Therefore, it is necessary to make the right decisions to carry out these activities, such as increasing the profit of businesses, improving the commercial strategies, and analyzing the industrial processes performance to produce better goods and services. This work proposes an intelligent system approach to prescribe actions and reduce the chemical oxygen demand (COD) in an equalizer tank of a wastewater treatment plant (WWTP) using machine learning models and genetic algorithms. There are three main objectives of this data-driven decision-making proposal. The first is to characterize and adapt a proper prediction model for the decision-making scheme. The second is to develop a prescriptive intelligent system based on expert’s rules and the selected prediction model’s outcomes. The last is to evaluate the system performance. As a novelty, this research proposes the use of long short-term memory (LSTM) artificial neural networks (ANN) with genetic algorithms (GA) for optimization in the WWTP area. |
| Databáze: | OpenAIRE |
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