Showing 161 - 180 results of 15,730 for search '(( algorithm a function ) OR ((( algorithm both function ) OR ( algorithm python function ))))', query time: 0.65s Refine Results
  1. 161

    The optimal solution set of NYN by using different algorithms. by Yi Tao (178829)

    Published 2022
    Subjects: “…evolutionary genetic algorithm…”
  2. 162

    The optimal solution set of HN by using different algorithms. by Yi Tao (178829)

    Published 2022
    Subjects: “…evolutionary genetic algorithm…”
  3. 163

    Algorithm for the treatment of external nasal valve insufficiency by Eduardo Landini Lutaif Dolci (10420109)

    Published 2021
    “…The diagnosis of nasal valve insufficiency remains a clinical one and is based on inspection and palpation of the nose, evaluating both its static and dynamic functions. …”
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    Table 6_Predictive prioritization of genes significantly associated with biotic and abiotic stresses in maize using machine learning algorithms.xlsx by Anjan Kumar Pradhan (9386369)

    Published 2025
    “…However, only one gene Zm00001eb038720 encoding RNA-binding protein AU-1/Ribonuclease E/G, predicted by the PLSDA algorithm, was found commonly expressed under both biotic and abiotic stress. …”
  6. 166

    Table 7_Predictive prioritization of genes significantly associated with biotic and abiotic stresses in maize using machine learning algorithms.xlsx by Anjan Kumar Pradhan (9386369)

    Published 2025
    “…However, only one gene Zm00001eb038720 encoding RNA-binding protein AU-1/Ribonuclease E/G, predicted by the PLSDA algorithm, was found commonly expressed under both biotic and abiotic stress. …”
  7. 167

    Table 3_Predictive prioritization of genes significantly associated with biotic and abiotic stresses in maize using machine learning algorithms.xlsx by Anjan Kumar Pradhan (9386369)

    Published 2025
    “…However, only one gene Zm00001eb038720 encoding RNA-binding protein AU-1/Ribonuclease E/G, predicted by the PLSDA algorithm, was found commonly expressed under both biotic and abiotic stress. …”
  8. 168

    Table 2_Predictive prioritization of genes significantly associated with biotic and abiotic stresses in maize using machine learning algorithms.xlsx by Anjan Kumar Pradhan (9386369)

    Published 2025
    “…However, only one gene Zm00001eb038720 encoding RNA-binding protein AU-1/Ribonuclease E/G, predicted by the PLSDA algorithm, was found commonly expressed under both biotic and abiotic stress. …”
  9. 169

    Table 1_Predictive prioritization of genes significantly associated with biotic and abiotic stresses in maize using machine learning algorithms.xlsx by Anjan Kumar Pradhan (9386369)

    Published 2025
    “…However, only one gene Zm00001eb038720 encoding RNA-binding protein AU-1/Ribonuclease E/G, predicted by the PLSDA algorithm, was found commonly expressed under both biotic and abiotic stress. …”
  10. 170

    Table 4_Predictive prioritization of genes significantly associated with biotic and abiotic stresses in maize using machine learning algorithms.xlsx by Anjan Kumar Pradhan (9386369)

    Published 2025
    “…However, only one gene Zm00001eb038720 encoding RNA-binding protein AU-1/Ribonuclease E/G, predicted by the PLSDA algorithm, was found commonly expressed under both biotic and abiotic stress. …”
  11. 171

    Table 5_Predictive prioritization of genes significantly associated with biotic and abiotic stresses in maize using machine learning algorithms.xlsx by Anjan Kumar Pradhan (9386369)

    Published 2025
    “…However, only one gene Zm00001eb038720 encoding RNA-binding protein AU-1/Ribonuclease E/G, predicted by the PLSDA algorithm, was found commonly expressed under both biotic and abiotic stress. …”
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  17. 177

    Data Sheet 1_A modified A* algorithm combining remote sensing technique to collect representative samples from unmanned surface vehicles.docx by Lei Wang (6656)

    Published 2024
    “…Water quality parameters were initially retrieved using satellite remote sensing imagery and a deep belief network model, with the parameter value incorporated as coefficient Q in the heuristic function of A* algorithm. …”
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  19. 179

    Overall process planning. by Dawei Wang (471687)

    Published 2025
    “…An innovative algorithm, the improved hybrid gray wolf and whale algorithm fused with a penalty function for construction machinery optimization (IHWGWO), is introduced, incorporating a penalty function to handle constraints effectively. …”
  20. 180

    Model intrinsic parameter flow. by Dawei Wang (471687)

    Published 2025
    “…An innovative algorithm, the improved hybrid gray wolf and whale algorithm fused with a penalty function for construction machinery optimization (IHWGWO), is introduced, incorporating a penalty function to handle constraints effectively. …”