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    Optimizing machine learning methods for groundwater quality prediction: Case study in District Bagh, Azad Kashmir, Pakistan by Usman Basharat, Wenjing Zhang, Cuihong Han, Shoukat Husain Khan, Arshad Abbasi, Sehrish Mahroof, Shuxin Li

    Published 2025-09-01
    “…Machine learning (ML) offers substantial potential for enhancing groundwater quality prediction, classification, and identification of pollution indicators. …”
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    A multifaceted comparative analysis of incremental dynamic and static pushover methods in bridge structural assessment, integrated with artificial neural network and genetic algori... by Ashwini Satyanarayana, V. Sindura, L. Geetha, Rakesh Kumar, Mohd Asif Shah, Mary Subaja Christo

    Published 2025-05-01
    “…The results of static pushover analysis and incremental dynamic analysis (IDA) are predicted and compared in this work using ANN and GA, which offers a deeper understanding of their predictive capabilities.…”
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  7. 1727

    Prediction of R1234yf flow boiling behavior in horizontal, vertical, and inclined tubes using machine learning techniques by Farzaneh Abolhasani, Behrang Sajadi, Mohammad Ali Akhavan-Behabadi

    Published 2025-05-01
    “…In the present study, the utilization of machine learning algorithms (MLAs) is proposed for the prediction of the heat transfer coefficient and pressure drop in horizontal, vertical, and inclined tubes during flow boiling of R1234yf. …”
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  8. 1728

    Proactive spectrum handoff in distributed cognitive radio networks by Hua JIANG, Li-chuan MA, Ding-yu YAN, Nan PAN

    Published 2014-11-01
    Subjects: “…distributed cognitive radio network;spectrum handoff;spectrum prediction;task allocation algorithm of ant colony…”
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    Modelling and Predicting the Breaking Strength and Mass Irregularity of Cotton Rotor-Spun Yarns Containing Cotton Fiber Recovered from Ginning Process by Using Artificial Neural Network Algorithm by Mohsen Shanbeh, Hossein Hasani, Somayeh Akhavan Tabatabaei

    Published 2011-01-01
    “…The purpose of this study was to develop predictive models of breaking strength and mass irregularity (CV𝑚%) of cotton waste rotor-spun yarns containing cotton waste collected from ginning process by using the artificial neural network trained with backpropagation algorithm. …”
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    A web-based tool for predicting gastric ulcers in Chinese elderly adults based on machine learning algorithms and noninvasive predictors: A national cross-sectional and cohort study by Xingjian Xiao, Xiaohan Yi, Zumin Shi, Zongyuan Ge, Hualing Song, Hailei Zhao, Tiantian Liang, Xinming Yang, Suxian Liu, Bo Sun, Xianglong Xu

    Published 2025-04-01
    “…We employed nine machine learning algorithms to construct predictive models for gastric ulcers over the next seven years (2011–2018, with 1482 samples) and the next three years (2014–2018, with 2659 samples). …”
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    Development of an algorithm to improve on the National Early Warning Score 2 (NEWS2) system's accuracy in predicting critical outcomes using additional patient data and amendments to the scoring process by Lynsey Threlfall, Chris Plummer, Edward Meinert, Cen Cong, Madison Milne-Ives

    Published 2025-07-01
    “…Using these datasets, we will train and test an algorithm that optimises the variables and their weightings to predict the risk of key clinical outcomes, including mortality, intensive care unit admission, sepsis and cardiac arrest, to demonstrate a proof of concept for a modified scoring system. …”
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