يعرض 81 - 100 نتائج من 48,614 نتيجة بحث عن '(( significant main decrease ) OR ( significant prediction based ))', وقت الاستعلام: 0.62s تنقيح النتائج
  1. 81

    500m scale main data of each grid. حسب Qingxi Shen (3547970)

    منشور في 2023
    "…Finally, in the context of scale differences, all types of coupling coordination degrees have significant sensitivity to the spatial scales. A large scale significantly reflects the overall decrease in the coupling coordination degrees from the core to the periphery, while a small scale shows the polycentric pattern characteristics of the urban spatial structure.…"
  2. 82

    1000m scale main data of each grid. حسب Qingxi Shen (3547970)

    منشور في 2023
    "…Finally, in the context of scale differences, all types of coupling coordination degrees have significant sensitivity to the spatial scales. A large scale significantly reflects the overall decrease in the coupling coordination degrees from the core to the periphery, while a small scale shows the polycentric pattern characteristics of the urban spatial structure.…"
  3. 83

    2000m scale main data of each grid. حسب Qingxi Shen (3547970)

    منشور في 2023
    "…Finally, in the context of scale differences, all types of coupling coordination degrees have significant sensitivity to the spatial scales. A large scale significantly reflects the overall decrease in the coupling coordination degrees from the core to the periphery, while a small scale shows the polycentric pattern characteristics of the urban spatial structure.…"
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    MEG main effect of material: Word-faces. حسب Marie-Christin Fellner (7053533)

    منشور في 2019
    "…<p>(A) Main effect of material: word versus face condition irrespective of memory: significant clusters (<i>p</i><sub>corr</sub> < 0.05) returned by a cluster permutation statistic clustering across sensors, frequencies (“Freq”), and channels. …"
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    Random Forest based prediction process. حسب Mohammed Majeed Hameed (14053535)

    منشور في 2025
    "…To address this, the study focuses on the Lotschental catchment in Switzerland, conducting a comprehensive comparison between deep learning and ensemble-based models. Given the significant autocorrelation in runoff time series data, which may hinder the evaluation of prediction models, a novel statistical method is employed to assess the effectiveness of forecasting models in detecting turning points in the runoff data. …"
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  20. 100

    Main components of bauxite and BCFD (wt.%). حسب Nian Liu (29935)

    منشور في 2025
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