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    Travel time prediction for an intelligent transportation system based on a data-driven feature selection method considering temporal correlation by Amirreza Kandiri, Ramin Ghiasi, Maria Nogal, Rui Teixeira

    Published 2024-12-01
    “…In this study, a two-stage methodology is proposed which consists of two layers of Optimisation Algorithm and one Data-Driven method (OA2DD) to enhance the accuracy and efficiency of travel-time prediction. …”
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  6. 1666

    Potential Biomarkers for Predicting the Risk of Developing Into Long COVID After COVID‐19 Infection by Zhiyong Hou, Yu Ming, Jun Liu, Zhong Wang

    Published 2025-01-01
    “…Among the 67 candidate genes were processed with machine learning algorithms and logistic regression, a subgroup consisting of CEP55, CDCA2, MELK, and DEPDC1B, was at last identified as potential biomarkers for predicting the risk of the progression into long COVID after COVID‐19 infections. …”
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    Integrating Bioengineering and Machine Learning: A Multi-Algorithm Approach to Enhance Agricultural Sustainability and Resource Efficiency by Senthil G.A., Prabha R., Asha R.M., Suganthi S.U., Sridevi S.

    Published 2025-01-01
    “…Findings have indicated that the multi-algorithm approach not only promotes increased predictive capabilities and resource optimization but also raises food safety with the increased threats in agriculture.…”
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    CPDGA: foresee future DGA using proactive conformal propagation by LIU Shuangshuang, WANG Zhi, DONG Yimeng, LI Wanpeng

    Published 2025-06-01
    Subjects: “…domain generation algorithm…”
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    Prediction of Breakdown Voltage of Long Air Gaps Under Switching Impulse Voltage Based on the ISSA-XGBoost Model by Zisheng Zeng, Bin Song, Shaocheng Wu, Yongwen Li, Deyu Nie, Linong Wang

    Published 2025-04-01
    “…To address this issue, this paper proposes a novel prediction model based on the Improved Sparrow Search Algorithm-optimized XGBoost (ISSA-XGBoost). …”
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    Algorithm for selecting predictors and prognosis of atrial fibrillation in patients with coronary artery disease after coronary artery bypass grafting by B. I. Geltser, K. I. Shakhgeldyan, V. Yu. Rublev, B. O. Shcheglov, E. A. Kokarev

    Published 2021-08-01
    “…These values in best model based on multivariate LR were lower (0,75; 0,7; 0,68 and 0,7, respectively).Conclusion. The developed algorithm for selecting predictors made it possible to verify significant predictive ranges and weight coefficients characterizing their influence on PAF development. …”
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