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  1. 1681

    Wireless Sensor Networks Focusing on Predicting Average Localization Error through Machine Learning Applications by Ioanna Gounari, Mattheos Kanzilieris

    Published 2024-09-01
    “…This research offers valuable insights into the effectiveness of different ML algorithms for predicting ALE in WSNs. By demonstrating the superior performance of DTRT, the study guides practitioners and researchers in selecting models that enhance localization accuracy, ultimately improving the overall functionality of WSNs.…”
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    Article
  2. 1682

    Development of machine learning models to predict the risk of fungal infection following flexible ureteroscopy lithotripsy by Haofang Zhang, Changbao Xu, Chenge Hu, Yunlai Xue, Daoke Yao, Yifan Hu, Ankang Wu, Miao Dai, Hang Ye

    Published 2025-04-01
    “…Our study aimed to construct a machine learning algorithm predictive model to predict the risk of fungal infection following F-URL. …”
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    Article
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  6. 1686

    Automatic Bone Fracture Reduction Technique with Section Registration by Qinhui YUAN, Mengxing LIU, Chu GUO, Yukun AN, Ping ZHOU

    Published 2025-01-01
    “…In order to enhance treatment efficiency and accuracy, an automatic fracture reduction algorithm is proposed. This algorithm utilizes the similarity of fracture cross-sections for registration, thereby reducing the workload of physicians and eliminating the need for a healthy-side bone template. …”
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    Article
  7. 1687
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    Optimal machine learning algorithms and UAV multispectral imagery for crop phenotypic trait estimation: a comprehensive review and meta-analysis by Adama Ndour, Gerald Blasch, João Valente, Bisrat Haile Gebrekidan, Tesfaye Shiferaw Sida

    Published 2025-01-01
    “…In this study, we conducted a comprehensive meta-analysis to analyze the relationship between the machine learning model performance and variables such crop type, the type of aerial phenotyping platform, the phenological stage, etc A trait-based comparison of the efficiency and popularity of machine learning algorithms was conducted. Our findings showed that the multiple linear regression is the most effective model in predicting biomass while artificial neural networks showed up as the top performing algorithm in determining nitrogen content. …”
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    Article
  9. 1689

    Improving Moth-Flame Optimization Algorithm by using Slime-Mould Algorithm by Sami N. Hussein, Nazar K. Hussein

    Published 2022-12-01
    “…The two predicted new algorithms were tested with standard test functions and the results were encouraging compared to the standard algorithms. …”
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    Article
  10. 1690
  11. 1691

    A Parallel Attribute Reduction Method Based on Classification by Deguang Li, Zhanyou Cui

    Published 2021-01-01
    “…Finally, the proposed algorithm and the traditional algorithm are analyzed and compared by experiments, and the results show that the proposed method in this paper has more advantages in time efficiency, which proves that the method could improve the processing efficiency of attribute reduction and makes it more suitable for massive data sets.…”
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  12. 1692
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  15. 1695

    Machine Learning for Predicting Required Cross-Sectional Dimensions of Circular Concrete-Filled Steel Tubular Columns by Anton Chepurnenko, Samir Al-Zgul, Vasilina Tyurina

    Published 2025-04-01
    “…The first and second models are based on the CatBoost algorithm. They predict the column diameter at minimum and maximum wall thicknesses, respectively. …”
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    Article
  16. 1696
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    Average Corrosion Rate Prediction Model for Buried Oil and Gas Pipelines Based on SSA-LightGBM by Weigang Fu, Haitao Wang, Kuankuan Zhang, Xia Wang, Kunlun Chen, Chunmei Sun, Zhengwei Wang, Liuyang Song, Niannian Wang

    Published 2025-01-01
    “…Corrosion represents a major cause of damage and leakage in oil and gas pipelines, making accurate corrosion rate prediction critical for operational safety. This study establishes an average corrosion rate prediction model using the Sparrow Search Algorithm-optimized Light Gradient Boosting Machine (SSA-LightGBM). …”
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    Article
  18. 1698

    The application of adaptive symmetry reduction for LTL model checking by I. V. Konnov, V. A. Zakharov

    Published 2010-12-01
    “…Adaptive symmetry reduction is a technique which exploits the similarity of com- ponents in systems of regular structure. …”
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    Article
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    All-Cause Mortality Risk in Elderly Patients with Femoral Neck and Intertrochanteric Fractures: A Predictive Model Based on Machine Learning by Min A, Liu Y, Fu M, Hou Z, Wang Z

    Published 2025-05-01
    Subjects: “…Mortality、Intertrochanteric fractures、Femoral neck fractures、Boruta algorithm、Machine learning、Prediction model…”
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    Article