يعرض 141 - 160 نتائج من 237 نتيجة بحث عن '(((( algorithm flow function ) OR ( algorithm spc function ))) OR ( algorithm python function ))', وقت الاستعلام: 0.41s تنقيح النتائج
  1. 141
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    Dataset of networks used in assessing the Troika algorithm for clique partitioning and community detection حسب Samin Aref (4683934)

    منشور في 2025
    "…Each network is provided in .gml format or .pkl format which can be read into a networkX graph object using standard functions from the networkX library in Python. For accessing other networks used in the study, please refer to the article for references to the primary sources of those network data.…"
  4. 144

    Software: Order-flow and long-memory in a simulated financial market حسب Shane Silverman (22497770)

    منشور في 2025
    "…Key scripts apply custom metaorder generation algorithms to the empirical data to estimate and compare the $\alpha$ and $\gamma$ exponents.…"
  5. 145

    Active Control of Laminar and Turbulent Flows Using Adjoint-Based Machine Learning حسب Xuemin Liu (20372739)

    منشور في 2024
    "…This dissertation extends and applies an adjoint-based machine learning method, the deep learning PDE augmentation method (DPM), for closed-loop active control on both laminar and turbulent flows. The end-to-end sensitivities for optimization are computed using adjoints of the governing equations without restriction on the terms that may appear in the objective function, which we construct using algorithmic differentiation applied to the flow solver. …"
  6. 146

    Data for "Saturation hysteresis during cyclic injections of immiscible fluids in porous media: an invasion percolation study" حسب Zhongzheng Wang (9762575)

    منشور في 2025
    "…A pore-resolved interface tracking algorithm for simulating multiphase flow in arbitrarily structured porous media. …"
  7. 147

    G4SNVHunter workflow for identifying variants that affect G4 formation. حسب Rongxin Zhang (1618159)

    منشور في 2025
    "…<b>(B)</b> Function-level schematic of the G4SNVHunter workflow, showing the relationships between key modules and their data flow. …"
  8. 148

    Recursive-Expansive Dynamics Frameworks Formalization with Negation Isolation and Inverse Zero Operators حسب Del Bel, Julian (21403013)

    منشور في 2025
    الموضوعات: "…Mathematical methods and special functions…"
  9. 149

    <b>Fig. 6 |</b> <b>Autonomous microrobot navigation upstream in a flow environment.</b> حسب Mahmoud Medany (20766911)

    منشور في 2025
    "…In stronger flow, initial difficulties lead to more negative rewards, but the algorithm shows significant improvement by 400,000 steps. …"
  10. 150

    Framework of MAPPO. حسب Jianbin Zheng (587000)

    منشور في 2025
    "…This paper first analyzes the H-beam processing flow and appropriately simplifies it, develops a reinforcement learning environment for multi-agent scheduling, and applies the rMAPPO algorithm to make scheduling decisions. …"
  11. 151

    The average completion time of each method. حسب Jianbin Zheng (587000)

    منشور في 2025
    "…This paper first analyzes the H-beam processing flow and appropriately simplifies it, develops a reinforcement learning environment for multi-agent scheduling, and applies the rMAPPO algorithm to make scheduling decisions. …"
  12. 152

    The connection of physical space. حسب Jianbin Zheng (587000)

    منشور في 2025
    "…This paper first analyzes the H-beam processing flow and appropriately simplifies it, develops a reinforcement learning environment for multi-agent scheduling, and applies the rMAPPO algorithm to make scheduling decisions. …"
  13. 153

    End-to-end data transmission delay. حسب Jianbin Zheng (587000)

    منشور في 2025
    "…This paper first analyzes the H-beam processing flow and appropriately simplifies it, develops a reinforcement learning environment for multi-agent scheduling, and applies the rMAPPO algorithm to make scheduling decisions. …"
  14. 154

    Production workflow of stiffened H-beams. حسب Jianbin Zheng (587000)

    منشور في 2025
    "…This paper first analyzes the H-beam processing flow and appropriately simplifies it, develops a reinforcement learning environment for multi-agent scheduling, and applies the rMAPPO algorithm to make scheduling decisions. …"
  15. 155

    Collision risk warning. حسب Jianbin Zheng (587000)

    منشور في 2025
    "…This paper first analyzes the H-beam processing flow and appropriately simplifies it, develops a reinforcement learning environment for multi-agent scheduling, and applies the rMAPPO algorithm to make scheduling decisions. …"
  16. 156

    Framework of rMAPPO. حسب Jianbin Zheng (587000)

    منشور في 2025
    "…This paper first analyzes the H-beam processing flow and appropriately simplifies it, develops a reinforcement learning environment for multi-agent scheduling, and applies the rMAPPO algorithm to make scheduling decisions. …"
  17. 157

    Data_and_model_files. حسب Jianbin Zheng (587000)

    منشور في 2025
    "…This paper first analyzes the H-beam processing flow and appropriately simplifies it, develops a reinforcement learning environment for multi-agent scheduling, and applies the rMAPPO algorithm to make scheduling decisions. …"
  18. 158

    Data Sheet 1_A machine-learning approach for pancreatic neoplasia classification based on plasma extracellular vesicles.pdf حسب Ioanna Angelioudaki (21177620)

    منشور في 2025
    "…Multiple studies explore how EVs size, surface biomarkers or content can determine their unique role and function in the recipient cell’s gene expression, metabolism and behavior affecting cancer development. …"
  19. 159
  20. 160

    IUTF Dataset(Enhanced): Enabling Cross-Border Resource for Analysing the Impact of Rainfall on Urban Transportation Systems حسب Xuhui Lin (19505503)

    منشور في 2025
    "…</p><h2>Data Structure</h2><p dir="ltr">The dataset is organized into four primary components:</p><ol><li><b>Road Network Data</b>: Topological representations including spatial geometry, functional classification, and connectivity information</li><li><b>Traffic Sensor Data</b>: Sensor metadata, locations, and measurements at both 5-minute and hourly resolutions</li><li><b>Precipitation Data</b>: Hourly meteorological information with spatial grid cell metadata</li><li><b>Derived Analytical Matrices</b>: Pre-computed structures for advanced spatial-temporal modelling and network analyses</li></ol><h2>File Formats</h2><ul><li><b>Tabular Data</b>: Apache Parquet format for optimal compression and fast query performance</li><li><b>Numerical Matrices</b>: NumPy NPZ format for efficient scientific computing</li><li><b>Total Size</b>: Approximately 2 GB uncompressed</li></ul><h2>Applications</h2><p dir="ltr">The IUTF dataset enables diverse analytical applications including:</p><ul><li><b>Traffic Flow Prediction</b>: Developing weather-aware traffic forecasting models</li><li><b>Infrastructure Planning</b>: Identifying vulnerable network components and prioritizing investments</li><li><b>Resilience Assessment</b>: Quantifying system recovery curves, robustness metrics, and adaptive capacity</li><li><b>Climate Adaptation</b>: Supporting evidence-based transportation planning under changing precipitation patterns</li><li><b>Emergency Management</b>: Improving response strategies for weather-related traffic disruptions</li></ul><h2>Methodology</h2><p dir="ltr">The dataset creation involved three main stages:</p><ol><li><b>Data Collection</b>: Sourcing traffic data from UTD19, road networks from OpenStreetMap, and precipitation data from ERA5 reanalysis</li><li><b>Spatio-Temporal Harmonization</b>: Comprehensive integration using novel algorithms for spatial alignment and temporal synchronization</li><li><b>Quality Assurance</b>: Rigorous validation and technical verification across all cities and data components</li></ol><h2>Code Availability</h2><p dir="ltr">Processing code is available at: https://github.com/viviRG2024/IUTDF_processing</p>…"