يعرض 181 - 200 نتائج من 271 نتيجة بحث عن '(( algorithm sphere function ) OR ( ((algorithm python) OR (algorithm flow)) function ))*', وقت الاستعلام: 0.30s تنقيح النتائج
  1. 181

    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. …"
  2. 182

    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. …"
  3. 183

    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. …"
  4. 184

    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. …"
  5. 185

    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. …"
  6. 186

    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. …"
  7. 187

    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. …"
  8. 188

    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. …"
  9. 189

    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. …"
  10. 190
  11. 191

    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>…"
  12. 192

    Data Sheet 1_Investigating neural markers of Alzheimer's disease in posttraumatic stress disorder using machine learning algorithms and magnetic resonance imaging.pdf حسب Gabriella Yakemow (20137758)

    منشور في 2024
    "…The objective of this study was to identify structural and functional neural changes in patients with PTSD that may contribute to the future development of AD.…"
  13. 193

    Mathematical modeling for the efficiency function of the Retiro small hydroelectric power plant turbine-generator set حسب Francisco Wellington Martins da Silva (19868345)

    منشور في 2024
    "…The Hessian matrix technique was also used to verify the critical points of the function. The critical point corresponding to a water head of 11.47 meters and a turbine flow of 145.1 m<sup>3</sup>/s presented the highest operational efficiency. …"
  14. 194

    Data Sheet 1_Simplified two-compartment neuron with calcium dynamics capturing brain-state specific apical-amplification, -isolation and -drive.pdf حسب Elena Pastorelli (7024235)

    منشور في 2025
    "…A machine learning evolutionary algorithm, guided by a set of fitness functions, selected parameters defining neurons that express the desired apical dendritic mechanisms. …"
  15. 195

    SPSS Data File for Sample 1. حسب Mariusz Zięba (21369920)

    منشور في 2025
    "…The response functions switch attention and processing to what is likely to be helpful in alleviating suffering, distress and need, called action. …"
  16. 196

    Indices of fit for two three-factor models. حسب Mariusz Zięba (21369920)

    منشور في 2025
    "…The response functions switch attention and processing to what is likely to be helpful in alleviating suffering, distress and need, called action. …"
  17. 197

    SPSS Data File for Sample 3. حسب Mariusz Zięba (21369920)

    منشور في 2025
    "…The response functions switch attention and processing to what is likely to be helpful in alleviating suffering, distress and need, called action. …"
  18. 198

    SPSS Data File for Sample 2. حسب Mariusz Zięba (21369920)

    منشور في 2025
    "…The response functions switch attention and processing to what is likely to be helpful in alleviating suffering, distress and need, called action. …"
  19. 199

    Nguyen Dupuis Network. حسب Anqi Jiang (4583380)

    منشور في 2025
    "…Then, the upper-level model is solved using improved whale optimization, and the lower-level model is solved using improved Frank-Wolfe algorithm. The results showed that the accuracy and recall of the proposed improved whale optimization algorithm on the Iris dataset were 95.27% and 92.65%, respectively, which were superior to traditional whale optimization algorithm, moth flame optimization algorithm, moth flame optimization algorithm combined with chaos strategy, and adaptive firefly optimization algorithm. …"
  20. 200

    Relative error iteration curve. حسب Anqi Jiang (4583380)

    منشور في 2025
    "…Then, the upper-level model is solved using improved whale optimization, and the lower-level model is solved using improved Frank-Wolfe algorithm. The results showed that the accuracy and recall of the proposed improved whale optimization algorithm on the Iris dataset were 95.27% and 92.65%, respectively, which were superior to traditional whale optimization algorithm, moth flame optimization algorithm, moth flame optimization algorithm combined with chaos strategy, and adaptive firefly optimization algorithm. …"