Showing 641 - 660 results of 1,432 for search 'Snapline~', query time: 2.53s Refine Results
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    Use of data mining algorithms in prediction of eggshell thickness from egg quality traits of Potchefstroom Koekoek layers by Kagisho Madikadike Molabe, Thobela Louis Tyasi, Vusi Gordon Mbazima

    Published 2025-01-01
    “…Study was conducted to compare performance of data mining algorithms; Classification and regression tree (CART), Chi-square automatic interaction detection (CHAID), Exhaustive chi-square automatic interaction detection (Ex-CHAID) and Multivariate adaptive regression spline (MARS) in prediction of Potchefstroom Koekoek’s eggshell thickness from egg quality traits. 350 eggs were collected at 31st to 39th week to examine the egg quality traits. …”
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    The association between non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio (NHHR) and sarcopenia: A cross-sectional study by Xiudeng Yang, Zheng Zhong

    Published 2025-02-01
    “…A multivariate logistic regression and a restricted cubic spline (RCS) model adjusted for associated factors were utilized to evaluate the correlation between NHHR and sarcopenia. …”
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    Spatial Interpolation of Daily Rainfall Data for Local Climate Impact Assessment over Greater Sydney Region by Xihua Yang, Xiaojin Xie, De Li Liu, Fei Ji, Lin Wang

    Published 2015-01-01
    “…Four common interpolation techniques (ANUDEM, Spline, IDW, and Kriging) were compared and assessed against station rainfall data and modeled rainfall. …”
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    Prediction of Mine Dust Concentration Based on Grey Markov Model by Zhou Xu, Guo Liwen, Zhang Jiuling, Qin Sijia, Zhu Yi

    Published 2021-01-01
    “…Firstly, considering the timeliness of monitoring data, the new dust concentration data is supplemented by using the method of cubic spline interpolation in the original data sequence. …”
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    Model of Driver’s Eye Movement and ECG Index under Tunnel Environment Based on Spatiotemporal Data by Weiwei Qi, Bin Shen, Linhong Wang

    Published 2020-01-01
    “…The results show that the cubic spline interpolation function model can fit the dynamic changes of average pupil diameter and heart rate (HR) growth rate well, and the goodness of fit for the model group is above 0.95. …”
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