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    Predicting diabetes using supervised machine learning algorithms on E-health records by Sulaiman Afolabi, Nurudeen Ajadi, Afeez Jimoh, Ibrahim Adenekan

    Published 2025-03-01
    “…Methods: This study investigates the early detection and management of diabetes by applying machine learning techniques to electronic health records. The research explores the effectiveness of three supervised machine learning algorithms: logistic regression, Random Forest, and k-nearest neighbors (KNN), in developing predictive models for diabetes. …”
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    The impact of rainfall and slope on hillslope runoff and erosion depending on machine learning by Naichang Zhang, Zhaohui Xia, Peng Li, Qitao Chen, Ganggang Ke, Fan Yue, Fan Yue, Yaotao Xu, Tian Wang

    Published 2025-04-01
    “…To address this gap, this study, based on machine learning methods, explores the effects of rainfall type, rainfall amount, maximum 30-min rainfall intensity (I30), and slope on hillslope runoff depth (H) and erosion-induced sediment yield (S), and unveils the interactions among these factors.MethodsThe K-means clustering algorithm was used to classify 43 rainfall events into three types: A-type, B-type, and C-type. …”
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    Research on Ship Heave Motion Compensation Control Under Complex Sea State Environment Based on Improved Reinforcement Learning by ZHANG Qin, ZHOU Jingyi, WANG Xingyue, HU Xiong

    Published 2025-07-01
    “…In these diversified test scenarios, the improved TD3 algorithm exhibits remarkable adaptability and stability. …”
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    Research on Cooperative Localization Method in Dynamic Networks by ZHANG Zhihua, SUN Bin, LI Bingchen, ZHOU Zhongfu, SHEN Feng

    Published 2024-12-01
    “…These circumstances can result in a decrease in the accuracy of cooperative localization algorithms or even cause them to malfunction. In order to address the above problems, this paper carries out the research on cooperative localization method, and proposes the filtering method of adaptive adjustment of observation error covariance matrix and the fusion of the federated filtering method, which enables the cooperative localization system to work normally in the case of the change of anchor nodes and ordinary nodes among mobile nodes, the disappearance or emergence of ranging values between nodes, and the random access and exit of nodes, etc. …”
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