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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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  3. 1503

    Advanced machine learning techniques for predicting compressive strength and ultrasonic pulse velocity of concrete incorporating industrial by-products by Ehsan Mohsennia, Alireza Javid, Vahab Toufigh

    Published 2025-07-01
    “…Among the models tested, the CatBoost (CB) algorithm, optimized with the Whale Optimization Algorithm (WOA), exhibited outstanding predictive performance. …”
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  4. 1504

    Research on short-term traffic flow prediction based on the PCC-IGA-LSTM model by Junxi Zhang, Shiru Qu, Yang Bi, Lijing Ma

    Published 2025-04-01
    “…To effectively address the spatial–temporal feature mining problem in short-term traffic flow prediction for complex road networks, a new method that combined the Pearson correlation coefficient (PCC) and improved genetic algorithm to optimize the long short-term memory model (IGA-LSTM) was constructed. …”
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  5. 1505
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    Construction and validation of a prognostic model for NK/T-cell lymphoma based on random survival forest algorithm by HUANG Zhen, HUANG Zhen, WU Yazhou

    Published 2025-02-01
    “…Objective‍ ‍To investigate the prognostic factors affecting survival in patients with natural killer T-cell lymphoma (NKTL), and then develop a prognostic model for predicting their overall survival (OS) based on random survival forest (RSF) algorithm. …”
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    Construction of a random survival forest model based on a machine learning algorithm to predict early recurrence after hepatectomy for adult hepatocellular carcinoma by Ji Zhang, Qing Chen, Yu Zhang, Jie Zhou

    Published 2024-12-01
    “…The present study aims to investigate the efficacy of the random survival forest (RSF) model, which is a machine learning algorithm, in predicting the early postoperative recurrence of HCC, and compare its performance with that of the traditional CPH model. …”
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  13. 1513

    Algorithm for predicting cardiovascular events in low/moderate risk patients using traditional and new factors: data from 10-year follow-up study by M. D. Smirnova, O. N. Svirida, T. V. Fofanova, Z. N. Blankova, E. B. Yarovaya, F. T. Ageev

    Published 2021-10-01
    “…To create an advanced algorithm for predicting cardiovascular events (CVE) in low/moderate risk patients using a complex of traditional and new factors.Material and methods. …”
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    Text Message System for the Prediction of Colonoscopy Bowel Preparation Adequacy Before Colonoscopy: An Artificial Intelligence Image Classification Algorithm Based on Images of Stool Output by Chethan Ramprasad, Divya Saini, Henry Del Carmen, Lev Krasnovsky, Rajat Chandra, Ryan Mcgregor, Russell T. Shinohara, Eric Eaton, Meghna Gummadi, Shivan Mehta, James D. Lewis

    Published 2025-01-01
    “…We aim to develop an artificial intelligence (machine learning) algorithm to assess photos of stool output after bowel preparation to predict inadequate bowel preparation before colonoscopy. …”
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  17. 1517

    Research on the Gas Emission Quantity Prediction Model of Improved Artificial Bee Colony Algorithm and Weighted Least Squares Support Vector Machine (IABC-WLSSVM) by Lei Wang, Jinghang Li, Wenbo Zhang, Yu Li

    Published 2022-01-01
    “…In order to further accurately predict gas emission of working face, this paper proposes a prediction model of gas emission of working face based on the combination of improved artificial bee colony algorithm and weighted least squares support vector machine (IABC-WLSSAVM). …”
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  18. 1518

    Application of Extra-Trees Regression and Tree-Structured Parzen Estimators Optimization Algorithm to Predict Blast-Induced Mean Fragmentation Size in Open-Pit Mines by Madalitso Mame, Shuai Huang, Chuanqi Li, Jian Zhou

    Published 2025-07-01
    “…The prediction accuracy of the models is optimized utilizing the tree-structured Parzen estimators (TPEs) algorithm, which results in three models: TPE-ET, TPE-GB, and TPE-RF. …”
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    Hybrid-driven modeling using a BiLSTM–AdaBoost algorithm for diameter prediction in the constant diameter stage of Czochralski silicon single crystals by Yu-Yu Liu, Ding Liu, Shi-Hai Wu, Yi-Ming Jing

    Published 2025-05-01
    “…Subsequently, the prediction results of the BiLSTM network are weighted and fused by the AdaBoost algorithm to obtain the final time series prediction output, and the prediction performance is further enhanced by iterative optimization. …”
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