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    Midspan Deflection Prediction of Long-Span Cable-Stayed Bridge Based on DIWPSO-SVM Algorithm by Lilin Li, Qing He, Hua Wang, Wensheng Wang

    Published 2025-05-01
    “…With the increasing emphasis on the safety and longevity of large-span cable-stayed bridges, the accurate prediction of midspan deflection has become a critical aspect of structural health monitoring (SHM). …”
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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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  6. 666

    APPLICATION OF SUGENO FUZZY INFERENCE ALGORITHM IN THE PROBLEM OF PREDICTING THE RESIDUAL LIFE OF AVIATION RADIOTECHNICAL EQUIPMENT by Trần Minh Hải, Ku Thanh Phong, Nguyen The Thang, Nguyễn Thanh Sáng, N.K. Yurkov, Phạm Văn Tú

    Published 2025-05-01
    “…The paper presents a theoretical representation of fuzzy logic, residual resource and the application of fuzzy-logical inference algorithms for solving the problems of extending and predicting the residual resource of aviation radio engineering devices. …”
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    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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  8. 668

    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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  9. 669

    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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    Research on Ship Engine Fuel Consumption Prediction Algorithm Based on Adaptive Optimization Generative Network by Defu Zhang, Yuxuan Song, Jianfeng Gao, Zhenyu Shen, Liangkuan Li, Anren Yao

    Published 2025-06-01
    “…The results are verified to be effective. The MD-RAN algorithm is significantly better than the original model in terms of prediction accuracy, stability, and nonlinear expression ability. …”
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    Lithium-ion battery RUL prediction based on optimized VMD-SSA-PatchTST algorithm by Pei Tang, Zetao Qiu, Zhongran Yao, Jiahao Pan, Dashuai Cheng, Xiaoyong Gu, Changcheng Sun

    Published 2025-07-01
    “…The selected features and decomposed components are subsequently input into a PatchTST network, whose hyperparameters are tuned via the Sparrow Search Algorithm (SSA), to predict battery RUL. Experimental validation on the NASA Battery dataset and NASA Randomized Battery Usage Dataset demonstrates that the proposed WOA-VMD-SSA-PatchTST model consistently outperforms baseline models, including CNN, GRU and PatchTST, achieving superior prediction accuracy and robustness.…”
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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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    Predictive modeling of adolescent suicidal behavior using machine learning: Key features and algorithmic insights by Priya Metri, Swetta Kukreja

    Published 2025-12-01
    “…Among these, Random Forest and SVM emerged as the most commonly used algorithms, featured in 35 % and 27 % of studies respectively. …”
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