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    Construction of a prediction model for moderate to severe perimenopausal syndrome based on machine learning algorithms by ZHANG Min, GU Tingting, GUAN Wei, LIU Xiangxiang, SHI Junyao

    Published 2024-08-01
    “…Objective To identify risk factors for perimenopausal syndrome (PMS) among perimenopausal women using machine learning algorithms, and to construct a predictive model for the risk of developing moderate to severe PMS in perimenopausal women. …”
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    Article
  5. 485

    Explainable and Interpretable Model for the Early Detection of Brain Stroke Using Optimized Boosting Algorithms by Yogita Dubey, Yashraj Tarte, Nikhil Talatule, Khushal Damahe, Prachi Palsodkar, Punit Fulzele

    Published 2024-11-01
    “…<b>Results:</b> The performance of three boosting algorithms is studied for stroke prediction, which include Gradient Boosting (GB), AdaBoost (ADB), and XGBoost (XGB) with XGB achieved the best outcome overall with a training accuracy of 96.97% and testing accuracy of 92.13%. …”
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    Design of weighted based divided-search enhanced Karnik–Mendel algorithms for type reduction of general type-2 fuzzy logic systems by Yang Chen

    Published 2025-02-01
    “…Here the weighted type-reduction algorithms based on the Newton and Cotes quadrature formulas of numerical methods of integration technique are first given, and the searching spaces are divided. …”
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    PREDICTIVE CONTROL SYSTEM SYNTHESIS OF DISTRICT HEATING SYSTEM by Dobrotin S.A., Prokopchuk E.L.

    Published 2011-08-01
    Subjects: “…predictive control…”
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    Comparing and Predicting Hepatic Encephalopathy Complications Using Random Forest Algorithm in Active Men by Bakhtyar Tartibian, Leila Fasihi, Rasoul Eslami, Ahmad Fasihi

    Published 2025-01-01
    “…Results: There was no significant difference in predicting encephalopathy complications by random forest algorithm between active and inactive men. …”
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    Dye-cleaning prediction with a variant of nature-inspired algorithms coupled with extreme gradient boosting by Tiyasha Tiyasha, Chijioke Elijah Onu, Mohamed A. Ismail, Rama Rao Karri, Abdelfattah Amari, Vinay Kumar, Suraj Kumar Bhagat

    Published 2025-07-01
    “…Hyperparameter tuning via differential evolution (DE), genetic algorithm (GA), random search (RS), and grid search (GS) with the XGBoost model was conducted to achieve more accurate results. …”
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    Nonlinear Volatility Risk Prediction Algorithm of Financial Data Based on Improved Deep Learning by Wangsong Xie

    Published 2022-01-01
    “…With the gradual integration of global economy and finance, the financial market presents many complex financial phenomena. To increase the prediction accuracy of financial data, a new nonlinear volatility risk prediction algorithm is proposed based on the improved deep learning algorithm. …”
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