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    A Comprehensive Review of Artificial Intelligence-Based Algorithms for Predicting the Remaining Useful Life of Equipment by Weihao Li, Jianhua Chen, Sijuan Chen, Peilin Li, Bing Zhang, Ming Wang, Ming Yang, Jipu Wang, Dejian Zhou, Junsen Yun

    Published 2025-07-01
    “…While significant advancements in computer hardware and artificial intelligence (AI) algorithms have catalyzed substantial progress in AI-based RUL prediction, extant research frequently exhibits a narrow focus on specific algorithms, neglecting a comprehensive and comparative analysis of AI techniques across diverse equipment types and operational scenarios. …”
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    Article
  4. 424

    A Clinical Risk Prediction Model for Depressive Disorders Based on Seven Machine Learning Algorithms by Jin W, Chen S, Wang M, Lin P

    Published 2025-05-01
    “…Univariate logistic regression analysis (p< 0.1) was initially performed to identify potential predictors, followed by feature selection using the Boruta and LASSO algorithms. Seven machine learning algorithms were employed to construct predictive models, with their performance evaluated using metrics such as AUC, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), precision, recall, and F1 score. …”
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  5. 425

    CLASSIFICATION AND PREDICTION OF BENTHIC HABITAT FROM SCIENTIFIC ECHOSOUNDER DATA: APPLICATION OF MACHINE LEARNING ALGORITHMS by Baigo HAMUNA, Sri PUJIYATI, Jonson Lumban GAOL, Totok HESTIRIANOTO

    Published 2024-12-01
    “…The classification and prediction process of benthic habitats uses two machine learning algorithms, Random Forest (RF) and Support Vector Machine (SVM), in XLSTAT Basic+ software. …”
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    Article
  6. 426

    Hybridization of Machine Learning Algorithms and an Empirical Regression Model for Predicting Debris-Flow-Endangered Areas by Xiang Wang, Mi Tian, Qiang Qin, Jingwei Liang

    Published 2023-01-01
    “…This paper proposes a hybrid method for predicting debris-flow hazard zone by integrating machine-learning algorithms and an empirical regression model. …”
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    Final weight prediction from body measurements in Kıvırcık lambs using data mining algorithms by Ö. Şengül, Ş. Çelik

    Published 2025-05-01
    “…The statistical performances of these algorithms (CHAID, exhaustive CHAID, CART, RF, MARS, and Bagging MARS) were tested by using several goodness-of-fit criteria, namely the coefficient of determination (<span class="inline-formula"><i>R</i><sup>2</sup>=0.699</span>, 0.699, 0.722, 0.662, 0.792, and 0.624), adjusted coefficient of determination (Adj.…”
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  9. 429

    DATA MINING ALGORITHMS FOR PREDICTION OF STUDENT TEACHERS’ PERFORMANCE IN ICT: A SYSTEMATIC LITERATURE REVIEW by Juma Habibu Shindo, Mohamedi Mohamedi Mjahidi, Mohamed Dewa Waziri

    Published 2023-09-01
    “…The aim of this article is to identify the appropriate Data Mining algorithms for predicting student teachers’ performance in ICT. …”
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    Article
  10. 430

    Heating Load Prediction with Meta-Heuristic ‎Algorithms and Adaptive Neuro-Fuzzy ‎Inference System Integration by Seyed Hadi Seyed Hatami, Reza Seifi Majdar

    Published 2025-03-01
    “…Addressing this need, this study adopts a holistic ap-proach by integrating advanced optimization algorithms with precise heating load prediction techniques. …”
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    Article
  11. 431

    Optimisation of Ensemble Learning Algorithms for Geotechnical Applications: A Mathematical Approach to Relative Density Prediction by Mahdy Khari, Ali Dehghanbanadaki, Danial Jahed Armaghani, Manoj Khandelwal

    Published 2025-01-01
    “…The challenge of predicting relative dry density (Dr) in granular materials is addressed through advanced mathematical modelling and machine learning (ML) techniques. …”
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    Prediction of Surface Settlement Induced by Large-Diameter Shield Tunneling Based on Machine-Learning Algorithms by Chao Li, Jinhui Li, Zhongqi Shi, Li Li, Mingxiong Li, Dianqi Jin, Guo Dong

    Published 2022-01-01
    “…Among the three machine-learning algorithms, the LSTM algorithm gives the best accuracy in predicting the maximum surface settlement and can effectively predict the settlement development in different strata.…”
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  14. 434

    Machine learning algorithms to predict stroke in China based on causal inference of time series analysis by Qizhi Zheng, Ayang Zhao, Xinzhu Wang, Yanhong Bai, Zikun Wang, Xiuying Wang, Xianzhang Zeng, Guanghui Dong

    Published 2025-05-01
    “…Conclusions and Relevance This study proposes a stroke risk prediction method that combines dynamic causal inference with machine learning models, significantly improving prediction accuracy and revealing key health factors that affect stroke. …”
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    Predicting suicidal behavior outcomes: an analysis of key factors and machine learning models by Mohammad Bazrafshan, Kourosh Sayehmiri

    Published 2024-11-01
    “…A combination of statistical models for feature selection and machine learning algorithms for prediction was used, with Random Forest showing the best performance. …”
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