يعرض 181 - 200 نتائج من 325 نتيجة بحث عن '(((( algorithm flow function ) OR ( algorithm pca function ))) OR ( algorithm python function ))', وقت الاستعلام: 0.47s تنقيح النتائج
  1. 181

    The fitness of NANEAT model evolution. حسب Wenbing Shi (5806160)

    منشور في 2025
    "…This paper proposes a CGO risk prediction method based on data augmentation and a neuroevolution algorithm, denoted as ANEAT. First, sample features are applied to the transfer function using a pointwise intensity transformation to obtain new feature samples. …"
  2. 182

    The speciation of NANEAT model evolution. حسب Wenbing Shi (5806160)

    منشور في 2025
    "…This paper proposes a CGO risk prediction method based on data augmentation and a neuroevolution algorithm, denoted as ANEAT. First, sample features are applied to the transfer function using a pointwise intensity transformation to obtain new feature samples. …"
  3. 183

    <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. …"
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  5. 185

    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. …"
  6. 186

    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. …"
  7. 187

    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. …"
  8. 188

    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. …"
  9. 189

    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. …"
  10. 190

    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. …"
  11. 191

    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. …"
  12. 192

    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. …"
  13. 193

    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. …"
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  17. 197

    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>…"
  18. 198

    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.…"
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    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. …"