Faculty of Technology Reports Findings in Machine Learning (Modelling coagulant dosage in drinking water treatment plant using advance machine learning model: Hybrid extreme learning machine optimized by Bat algorithm)

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Faculty of Technology Reports Findings in Machine Learning (Modelling coagulant dosage in drinking water treatment plant using advance machine learning model: Hybrid extreme learning machine optimized by Bat algorithm)

机译：Faculty of Technology Reports Findings in Machine Learning (Modelling coagulant dosage in drinking water treatment plant using advance machine learning model: Hybrid extreme learning machine optimized by Bat algorithm)

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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews – New research on Machine Learning is the subject of a report. According to news originating fromAnnaba, Algeria, by NewsRx correspondents, research stated, “Despite the high importance of coagulationprocess in drinking water treatment plant (DWTP), challenge remains in effectively linking raw waterquality measured at the inlet of the DWTP with coagulant dosage rate. This study proposes an integralmodelling framework using hybrid extreme learning machine and Bat metaheuristic algorithm (ELM-Bat)for modelling coagulant dosage rate using water temperature, pH, specific conductance, dissolved oxygen,and water turbidity.”

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《Robotics & Machine Learning Daily News》 |2023年第24期|42-42|共1页
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Annaba; Algeria; Africa; Algorithms; Cyborgs; Emerging Technologies; Machine Learning;

Faculty of Technology Reports Findings in Machine Learning (Modelling coagulant dosage in drinking water treatment plant using advance machine learning model: Hybrid extreme learning machine optimized by Bat algorithm)

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