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  1. 261

    A Review of Wind Power Prediction Methods Based on Multi-Time Scales by Fan Li, Hongzhen Wang, Dan Wang, Dong Liu, Ke Sun

    Published 2025-03-01
    “…Common classification angles of wind power prediction methods are outlined. By synthesizing existing approaches through multi-time scales, from the ultra-short term and short term to mid-long term, the review further deconstructs methods by model characteristics, input data types, spatial scales, and evaluation metrics. …”
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    Article
  2. 262

    Evaluation of Lightning Prediction by an Electrification and Discharge Model in Long-Term Forecasting Experiments by Liangtao Xu, Shuang Chen, Wen Yao

    Published 2022-01-01
    “…The numerical forecast results were evaluated using the neighborhood-based equitable threat score (ETS) and fraction skill score (FSS) verification methods based on nationwide observational lightning data. …”
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    Article
  3. 263
  4. 264

    AI-driven fall risk prediction in inpatients: Development, validation, and comparative evaluation by Chia-Lun Lo, Chia-En Liu, Hsiao Yun Chang, Chiu-Hsiang Wu

    Published 2025-03-01
    “…This study developed an AI-based fall risk prediction model using supervised learning techniques to enhance predictive accuracy and clinical integration. …”
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    Article
  5. 265
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  7. 267

    THE INFLUENCE OF ECOLOGICAL RISK FACTORS ON MORTALITY IN MOSCOW POPULATION. RISK EVALUATION AND PREDICTION by S. A. Boytsov, M. M. Lukyanov, A. D. Deev, V. G. Klyashtorny, A. V. Ivanenko, N. S. Volkova, A. S. Kuznetsov, A. S. Skvortsov, D. V. Solovyev

    Published 2016-06-01
    “…To assess the influence of temperature, humidity, air pollution on the mortality ofMoscowinhabitants in 2007-2014, to evaluate the possibility of mortality prediction by mathematic modelling.Material and methods. …”
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    Article
  8. 268

    Methods to evaluate the performance of a multicomponent meningococcal serogroup B vaccine by Ray Borrow, Laura Tomasi Cont, Daniela Toneatto, Stefania Bambini, Shravani Bobde, Woo-Yun Sohn, Alessia Biolchi, Vega Masignani, Peter T. Beernink, Maria Lattanzi

    Published 2025-04-01
    “…Traditional hSBA assay against a limited panel of strains is useful at all stages, while predicted strain coverage methods, such as the meningococcal antigen typing system, are used independent of clinical trials. …”
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    Article
  9. 269

    COMPARATIVE ESTIMATION OF SEMICONDUCTOR DICE MOUNTING ALTERNATE NONDESTRUCTIVE EVALUATION METHODS by S. S. Wolkenstein, I. V. Dayniak, A. A. Khmyl

    Published 2019-06-01
    “…Conventional method of nondestructive control - laser microinterferometry, which possibilities have been earlier expanded concerning to study “semiconductor chip - substrate” assemblies peculiarity, has given the chance to evaluate these assemblies stability to mechanical, electric and thermal loadings and to predict operational reliability of prefabricated production of electronic technics and microelectronics. …”
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    Article
  10. 270
  11. 271

    Evaluation of the Methods for Estimating the Fully Reversed Unnotched Fatigue Limits of Steels by Jing Li, Yuan-ying Qiu, Hai-dong Wang, Zhao-xi Wang

    Published 2019-01-01
    “…In this study, ten estimation methods are evaluated and compared using the experimental data of 171 steels from literature. …”
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    Article
  12. 272
  13. 273

    A Storm Frame Optimization Method for Predicting and Warning the Safety Status of a Shearer by Pei Zhang, Yanpeng He, Li Ma, Changkui Cong

    Published 2025-01-01
    “…The prediction accuracy, early warning accuracy, and processing efficiency of the Storm platform are used as evaluation indicators to analyze and evaluate the model, verifying the efficiency and applicability of the proposed model. …”
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    Article
  14. 274

    Significance of nuclear medicine methods for diagnosis and predicting the course of renal transplantation complications by M.V. Satyr, I.V. Noverko, T.I. Pantus, M.S. Zagriichuk

    Published 2023-12-01
    “…We pay the main attention to the nuclear medicine methods, especially the dynamic renal scintigraphy (DRSG) as a method for the evaluation of graft functionality. …”
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    Article
  15. 275

    Biomarkers for predicting efficacy of chimeric antigen receptor T cell therapy and their detection methods by Bo Zou, Yanzhou Song, Ning Li, Zhongyi Fan, Jie Li, Yuanzheng Peng, Wanshan Wei, Yuzi Zhang, Yinan Su, Xianmin Meng, Hongzhou Lu, Xingding Zhang, Xiaohua Tan, Qibin Liao

    Published 2024-03-01
    “…Thus, the primary objective of this review article was to provide a comprehensive overview of the factors predicting the efficacy of CAR‐T cell therapy, with a particular focus on biomarkers and their detection methods.…”
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    Article
  16. 276

    Explaining the Earnings Management Prediction Model Using the Hybrid of Machine Learning Methods by Hassan Hassani, Esfandiar Malekian Kallehbasti, Yahya Kamyabi

    Published 2024-08-01
    “…The performance of each machine learning method at predicting accrual-based earnings management and real earnings management was evaluated based on three criteria: type Ι error, type ΙΙ error, and average accurac.FindingThe results show that the performance of accrual-based earnings management forecasting methods based on the relief-based feature selection model is better than the feature selection model based on principal component analysis. …”
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  17. 277

    Overview of Applications and Research Directions of Deep Learning Methods for Wind Power Prediction by LIU Tan, LIU Na, LIU Guiping, LIU Kunjie, LIU Min, ZHUANG Xufei, ZHANG Zhonghao

    Published 2025-03-01
    “…This paper outlines the research objectives of wind power prediction from the classification of wind power prediction, the general idea of implementation, and the evaluation method. …”
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    Review of Spot Electricity Price Prediction Studies Based on Machine Learning Methods by JIA Heping, GUO Yuchen, MA Qianxin, YANG Zhenglin, ZHENG Yaxian, ZENG Dan, LIU Dunnan

    Published 2025-02-01
    “…This study then analyzed the evaluation criteria for spot electricity price prediction models based on machine learning, and summarized the model hyperparameter training requirements and the practical application of relevant prediction methods. …”
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    Article