بدائل البحث:
algorithm python » algorithm within (توسيع البحث), algorithms within (توسيع البحث), algorithm both (توسيع البحث)
python function » protein function (توسيع البحث)
flow function » from function (توسيع البحث), low functional (توسيع البحث), loss function (توسيع البحث)
algorithm pca » algorithm a (توسيع البحث), algorithm cl (توسيع البحث), algorithm co (توسيع البحث)
pca function » gpcr function (توسيع البحث), a function (توسيع البحث), fc function (توسيع البحث)
algorithm python » algorithm within (توسيع البحث), algorithms within (توسيع البحث), algorithm both (توسيع البحث)
python function » protein function (توسيع البحث)
flow function » from function (توسيع البحث), low functional (توسيع البحث), loss function (توسيع البحث)
algorithm pca » algorithm a (توسيع البحث), algorithm cl (توسيع البحث), algorithm co (توسيع البحث)
pca function » gpcr function (توسيع البحث), a function (توسيع البحث), fc function (توسيع البحث)
-
181
The fitness of NANEAT model evolution.
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. …"
-
182
The speciation of NANEAT model evolution.
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. …"
-
183
<b>Fig. 6 |</b> <b>Autonomous microrobot navigation upstream in a flow environment.</b>
منشور في 2025"…In stronger flow, initial difficulties lead to more negative rewards, but the algorithm shows significant improvement by 400,000 steps. …"
-
184
-
185
Framework of MAPPO.
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. …"
-
186
The average completion time of each method.
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. …"
-
187
The connection of physical space.
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. …"
-
188
End-to-end data transmission delay.
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. …"
-
189
Production workflow of stiffened H-beams.
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. …"
-
190
Collision risk warning.
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. …"
-
191
Framework of rMAPPO.
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. …"
-
192
Data_and_model_files.
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. …"
-
193
Data Sheet 1_A machine-learning approach for pancreatic neoplasia classification based on plasma extracellular vesicles.pdf
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. …"
-
194
-
195
-
196
-
197
IUTF Dataset(Enhanced): Enabling Cross-Border Resource for Analysing the Impact of Rainfall on Urban Transportation Systems
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>…"
-
198
Data Sheet 1_Investigating neural markers of Alzheimer's disease in posttraumatic stress disorder using machine learning algorithms and magnetic resonance imaging.pdf
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.…"
-
199
-
200
Mathematical modeling for the efficiency function of the Retiro small hydroelectric power plant turbine-generator set
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. …"