首页|Study Findings on Machine Learning Described by a Researcher at Chungbuk Nationa l University (Machine learning regression-based prediction model for the autonom ous control of coagulant dosing in smart water purification plants)
Study Findings on Machine Learning Described by a Researcher at Chungbuk Nationa l University (Machine learning regression-based prediction model for the autonom ous control of coagulant dosing in smart water purification plants)
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2024 OCT 03 (NewsRx)-By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Current study results on artificial in telligence have been published. According to news originating from Chungbuk, Sou th Korea, by NewsRx editors, the research stated, "ABSTRACT: The global issue of water scarcity is escalating due to urbanization and increased demand." Funders for this research include Ministry of Education. The news reporters obtained a quote from the research from Chungbuk National Uni versity: "This paper proposes a machine learning (ML) regression-based model for automatic coagulant dosing control in smart water purification plants (SWPPs).1 The model uses random forest (RF), light gradient boosting machine (LGBM), extr eme gradient boosting (XGB), and k-nearest neighbors (KNN) algorithms. Performan ce metrics include MAE, MSE, RMSE, MAPE, and R2. The RF algorithm showed superio r performance, with MAE of 0.005, MSE of 0.002, RMSE of 0.05, and MAPE of 0.000 for anion-poly aluminum chloride dosing, and MAE of 0.007, MSE of 0.00, RMSE of 0.02, and MAPE of 0.000 for Polymax dosing. The RF model's performance is due to its robust handling of large datasets and ensemble learning approach."
Chungbuk National UniversityChungbukSouth KoreaAsiaCyborgsEmerging TechnologiesMachine Learning
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