首页|Study Data from Singapore University of Technology and Design Provide New Insigh ts into Machine Learning (Fusing Design and Machine Learning for Anomaly Detecti on in Water Treatment Plants)
Study Data from Singapore University of Technology and Design Provide New Insigh ts into Machine Learning (Fusing Design and Machine Learning for Anomaly Detecti on in Water Treatment Plants)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on artificial intelligenc e is the subject of a new report. According to news originating from Singapore, Singapore, by NewsRx editors, the research stated, "Accurate detection of proces s anomalies is crucial for maintaining reliable operations in critical infrastru ctures such as water treatment plants." Funders for this research include National Research Foundation. The news editors obtained a quote from the research from Singapore University of Technology and Design: "Traditional methods for creating anomaly detection syst ems in these facilities typically focus on either design-based strategies, which encompass physical and engineering aspects, or on data-driven models that utili ze machine learning to interpret complex data patterns. Challenges in creating t hese detectors arise from factors such as dynamic operating conditions, lack of design knowledge, and the complex interdependencies among heterogeneous componen ts. This paper proposes a novel fusion detector that combines the strengths of b oth design-based and machine learning approaches for accurate detection of proce ss anomalies."
Singapore University of Technology and D esignSingaporeSingaporeAsiaCyborgsEmerging TechnologiesMachine Learn ing
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