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Application of ELM to predict the coagulant dosing in water treatment plants
- Source :
- Water Supply. 17:1053-1061
- Publication Year :
- 2016
- Publisher :
- IWA Publishing, 2016.
-
Abstract
- Predicting the coagulant dosage is especially crucial to the purification process in water treatment plants, directly affecting the quality of the purified water. Nowadays, several mathematical methods have been adopted for the purification process, but their predictive precision and speed still need to be improved. This study applies a novel neural network called the extreme learning machine (ELM) to predict the coagulant dosage based on certain signification factors of the raw water. Performances are compared between ELM and back-propagation neural networks in this paper. The results show that both neural network algorithms perform well in this application and ELM can realize online prediction due to its short time consumption.
- Subjects :
- Engineering
Artificial neural network
business.industry
Environmental engineering
02 engineering and technology
010501 environmental sciences
01 natural sciences
Purified water
0202 electrical engineering, electronic engineering, information engineering
020201 artificial intelligence & image processing
Water treatment
Raw water
business
Process engineering
0105 earth and related environmental sciences
Water Science and Technology
Extreme learning machine
Subjects
Details
- ISSN :
- 16070798 and 16069749
- Volume :
- 17
- Database :
- OpenAIRE
- Journal :
- Water Supply
- Accession number :
- edsair.doi...........1809004a22e37f8b5332ac8433664b55