يعرض 101 - 120 نتائج من 232 نتيجة بحث عن '(( significant decrease decrease ) OR ( significant ((mean decrease) OR (linear decrease)) ))~', وقت الاستعلام: 0.40s تنقيح النتائج
  1. 101
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  5. 105

    Results of the LMM analysis for IOP change. حسب Sayaka Kimura-Uchida (22793666)

    منشور في 2025
    "…The mean GMS was 2.46 ± 1.33 preoperatively, and decreased to 1.32 ± 1.31 at 3 months, and 1.60 ± 1.41 at 12 months postoperatively. …"
  6. 106

    Results of the LMM analysis for GMS change. حسب Sayaka Kimura-Uchida (22793666)

    منشور في 2025
    "…The mean GMS was 2.46 ± 1.33 preoperatively, and decreased to 1.32 ± 1.31 at 3 months, and 1.60 ± 1.41 at 12 months postoperatively. …"
  7. 107
  8. 108
  9. 109

    Cross-sectional dependence results. حسب Ozlem Kutlu Furtuna (20308206)

    منشور في 2024
    "…Moreover, FDI and the non-linear form of FDI have no significant influence on ecological footprint. …"
  10. 110

    Autocorrelation test results. حسب Ozlem Kutlu Furtuna (20308206)

    منشور في 2024
    "…Moreover, FDI and the non-linear form of FDI have no significant influence on ecological footprint. …"
  11. 111

    Pesaran’s CADF test results for Model I. حسب Ozlem Kutlu Furtuna (20308206)

    منشور في 2024
    "…Moreover, FDI and the non-linear form of FDI have no significant influence on ecological footprint. …"
  12. 112

    Descriptive statistics of related variables. حسب Ozlem Kutlu Furtuna (20308206)

    منشور في 2024
    "…Moreover, FDI and the non-linear form of FDI have no significant influence on ecological footprint. …"
  13. 113

    Performance comparison of ML models. حسب Gourab Saha (8987405)

    منشور في 2025
    "…Multi-spectral band images from Landsat-8 satellite images of a chosen land are employed from USGS Earth Resources Observation and Science (EROS) Center for extracting indices that are used for agricultural analysis, determining the vegetation index, water index, and salinity index of that land using K-means. Furthermore, crop yield is predicted using Linear Regression and Random Forest, achieving accuracies of 93.49% and 95.87%, respectively, while using RMSE (Root Mean Squared Error) as the loss function. …"
  14. 114

    Comparative data of different soil samples. حسب Gourab Saha (8987405)

    منشور في 2025
    "…Multi-spectral band images from Landsat-8 satellite images of a chosen land are employed from USGS Earth Resources Observation and Science (EROS) Center for extracting indices that are used for agricultural analysis, determining the vegetation index, water index, and salinity index of that land using K-means. Furthermore, crop yield is predicted using Linear Regression and Random Forest, achieving accuracies of 93.49% and 95.87%, respectively, while using RMSE (Root Mean Squared Error) as the loss function. …"
  15. 115

    Confusion matrix of random forest model. حسب Gourab Saha (8987405)

    منشور في 2025
    "…Multi-spectral band images from Landsat-8 satellite images of a chosen land are employed from USGS Earth Resources Observation and Science (EROS) Center for extracting indices that are used for agricultural analysis, determining the vegetation index, water index, and salinity index of that land using K-means. Furthermore, crop yield is predicted using Linear Regression and Random Forest, achieving accuracies of 93.49% and 95.87%, respectively, while using RMSE (Root Mean Squared Error) as the loss function. …"
  16. 116

    Sensor value scenario for fuzzy logic algorithm. حسب Gourab Saha (8987405)

    منشور في 2025
    "…Multi-spectral band images from Landsat-8 satellite images of a chosen land are employed from USGS Earth Resources Observation and Science (EROS) Center for extracting indices that are used for agricultural analysis, determining the vegetation index, water index, and salinity index of that land using K-means. Furthermore, crop yield is predicted using Linear Regression and Random Forest, achieving accuracies of 93.49% and 95.87%, respectively, while using RMSE (Root Mean Squared Error) as the loss function. …"
  17. 117

    Evaluation metrics of selected ML models. حسب Gourab Saha (8987405)

    منشور في 2025
    "…Multi-spectral band images from Landsat-8 satellite images of a chosen land are employed from USGS Earth Resources Observation and Science (EROS) Center for extracting indices that are used for agricultural analysis, determining the vegetation index, water index, and salinity index of that land using K-means. Furthermore, crop yield is predicted using Linear Regression and Random Forest, achieving accuracies of 93.49% and 95.87%, respectively, while using RMSE (Root Mean Squared Error) as the loss function. …"
  18. 118

    Block diagram of the proposed system. حسب Gourab Saha (8987405)

    منشور في 2025
    "…Multi-spectral band images from Landsat-8 satellite images of a chosen land are employed from USGS Earth Resources Observation and Science (EROS) Center for extracting indices that are used for agricultural analysis, determining the vegetation index, water index, and salinity index of that land using K-means. Furthermore, crop yield is predicted using Linear Regression and Random Forest, achieving accuracies of 93.49% and 95.87%, respectively, while using RMSE (Root Mean Squared Error) as the loss function. …"
  19. 119

    Chart for applicable amount of fertilizers. حسب Gourab Saha (8987405)

    منشور في 2025
    "…Multi-spectral band images from Landsat-8 satellite images of a chosen land are employed from USGS Earth Resources Observation and Science (EROS) Center for extracting indices that are used for agricultural analysis, determining the vegetation index, water index, and salinity index of that land using K-means. Furthermore, crop yield is predicted using Linear Regression and Random Forest, achieving accuracies of 93.49% and 95.87%, respectively, while using RMSE (Root Mean Squared Error) as the loss function. …"
  20. 120

    Cost analysis of irrigation controller unit. حسب Gourab Saha (8987405)

    منشور في 2025
    "…Multi-spectral band images from Landsat-8 satellite images of a chosen land are employed from USGS Earth Resources Observation and Science (EROS) Center for extracting indices that are used for agricultural analysis, determining the vegetation index, water index, and salinity index of that land using K-means. Furthermore, crop yield is predicted using Linear Regression and Random Forest, achieving accuracies of 93.49% and 95.87%, respectively, while using RMSE (Root Mean Squared Error) as the loss function. …"