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  1. 41

    Proposal for Using AI to Assess Clinical Data Integrity and Generate Metadata: Algorithm Development and Validation by Caroline Bönisch, Christian Schmidt, Dorothea Kesztyüs, Hans A Kestler, Tibor Kesztyüs

    Published 2025-06-01
    “…Logistic regression, k-nearest neighbors, a naive bayes classifier, a decision tree classifier, a random forest classifier, extreme gradient boosting (XGB), and support vector machines (SVM) were selected as machine learning algorithms. …”
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    Article
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    A Novel Toolbox for Generating Realistic Biological Cell Geometries for Electromagnetic Microdosimetry by Mehrdad Saviz, A.H. Buchali Safiee, Elham Sharifi

    Published 2020-06-01
    “…We have designed a free, user-friendly tool in MATLAB that combines several known or new algorithms for easy production of three-dimensional complex cell shapes based on minimum data. …”
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    Rapid diagnosis of power battery faults in new energy vehicles based on improved boosting algorithm and big data by Jiali Wang, Jia Chen

    Published 2024-12-01
    “…Subsequently, the importance of indicators in the data was analyzed using the Random Forest algorithm (RF). Finally, three improved Boosting algorithms were proposed, namely Light Gradient Boosting Machine (LightGBM), eXtreme Gradient Boosting Tree (XGBoost), and Gradient Boosting Decision Tree (CatBoost). …”
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    Article
  7. 47

    Optimizing Kernel Extreme Learning Machine based on a Enhanced Adaptive Whale Optimization Algorithm for classification task. by ZeSheng Lin

    Published 2025-01-01
    “…Furthermore, inspired by the grey wolf optimization algorithm, use 3 excellent particle surround strategies instead of the original random selecting particles. …”
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    Article
  8. 48

    Three-Dimensional Trajectory Tracking Control for Stratospheric Airship Based on Deep Reinforcement Learning by Xixiang Yang, Fangchao Bai, Xiaowei Yang, Yuelong Pan

    Published 2025-01-01
    “…The Boltzmann random distribution of reward value and probability of wind direction angle were taken as the action selection criteria of the Q-learning algorithm, the cerebellar model articulation controller (CMAC) neural network was constructed for the discrete action value, and the optimal action sequence was fast obtained. …”
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    Optimization of electric vehicle charging facility layout considering the enhancement of renewable energy consumption capacity and improvement of PSO algorithm by Di Zheng, Baobao Zheng

    Published 2025-04-01
    “…To deal with the optimization model, the particle swarm optimization is adopted and improved in three aspects. These three improvements include randomly updating inertia weights, introducing acceleration factors to replace learning factors, and introducing fast non-dominated sorting for better or worse selection, and improving the optimization ability of the algorithm by solving the crowding distance. …”
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    Use of Machine Learning to Predict the Incidence of Type 2 Diabetes Among Relatively Healthy Adults: A 10-Year Longitudinal Study in Taiwan by Ying-Qiang Liu, Tzu-Wei Chang, Lung-Chun Lee, Chia-Yu Chen, Pi-Shan Hsu, Yu-Tse Tsan, Chao-Tung Yang, Wei-Min Chu

    Published 2024-12-01
    “…Ultimately, 6687 adults were included in the final analysis, where we implemented three different ML algorithms, including logistic regression (LR), random forest (RF) and extreme gradient boosting (XGBoost) in order to predict diabetes. …”
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    Article
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