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An efficient neural network model for aiding the coagulation process of water treatment plants

Research article (Environment Development and Sustainability, 2021) · cited 17× · AI/ML
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An efficient neural network model for aiding the coagulation process of water treatment plants

Summary

An efficient neural network model for aiding the coagulation process of water treatment plants is a scholarly article[1].

Key Facts

  • An efficient neural network model for aiding the coagulation process of water treatment plants's instance of is recorded as scholarly article[2].

References

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Direct Wikidata claims

  1. [2] ↑ . wikidata.org.

Class ancestry

  1. [1] ↑ . Wikidata. wikidata.org.

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APA 4ort.xyz Knowledge Graph. (2026). An efficient neural network model for aiding the coagulation process of water treatment plants. Retrieved May 24, 2026, from https://4ort.xyz/entity/an-efficient-neural-network-model-for-aiding-the-coagulation-process-of-water-treatment-plants
MLA “An efficient neural network model for aiding the coagulation process of water treatment plants.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/an-efficient-neural-network-model-for-aiding-the-coagulation-process-of-water-treatment-plants.
BibTeX @misc{4ortxyz_an-efficient-neural-network-model-for-aiding-the-coagulation-process-of-water-treatment-plants_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{An efficient neural network model for aiding the coagulation process of water treatment plants}}, year = {2026}, url = {https://4ort.xyz/entity/an-efficient-neural-network-model-for-aiding-the-coagulation-process-of-water-treatment-plants}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): An efficient neural network model for aiding the coagulation process of water treatment plants — https://4ort.xyz/entity/an-efficient-neural-network-model-for-aiding-the-coagulation-process-of-water-treatment-plants (retrieved 2026-05-24)

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