Search alternatives:
algorithms within » algorithm within (Expand Search)
algorithm models » algorithm model (Expand Search)
algorithm python » algorithm within (Expand Search), algorithm both (Expand Search)
models function » model function (Expand Search), module function (Expand Search), mobius function (Expand Search)
algorithms within » algorithm within (Expand Search)
algorithm models » algorithm model (Expand Search)
algorithm python » algorithm within (Expand Search), algorithm both (Expand Search)
models function » model function (Expand Search), module function (Expand Search), mobius function (Expand Search)
-
1
<b>Opti2Phase</b>: Python scripts for two-stage focal reducer
Published 2025“…</p><p dir="ltr">The package includes:</p><ul><li>Scripts for first-order analysis, third-order modeling, optimization using a Physically Grounded Merit Function (PGMF), and RMS-based refinement.…”
-
2
-
3
Reward function related parameters.
Published 2025“…Hardware-in-the-loop (HIL) validation confirms the algorithm’s robustness under extreme conditions, with lateral stability metrics maintained within safety thresholds.…”
-
4
Steering system model.
Published 2025“…Hardware-in-the-loop (HIL) validation confirms the algorithm’s robustness under extreme conditions, with lateral stability metrics maintained within safety thresholds.…”
-
5
Braking system model.
Published 2025“…Hardware-in-the-loop (HIL) validation confirms the algorithm’s robustness under extreme conditions, with lateral stability metrics maintained within safety thresholds.…”
-
6
Main parameters of braking system.
Published 2025“…Hardware-in-the-loop (HIL) validation confirms the algorithm’s robustness under extreme conditions, with lateral stability metrics maintained within safety thresholds.…”
-
7
EMB and SBW system structure.
Published 2025“…Hardware-in-the-loop (HIL) validation confirms the algorithm’s robustness under extreme conditions, with lateral stability metrics maintained within safety thresholds.…”
-
8
Raw data.
Published 2025“…Hardware-in-the-loop (HIL) validation confirms the algorithm’s robustness under extreme conditions, with lateral stability metrics maintained within safety thresholds.…”
-
9
Code program.
Published 2025“…Hardware-in-the-loop (HIL) validation confirms the algorithm’s robustness under extreme conditions, with lateral stability metrics maintained within safety thresholds.…”
-
10
The HIL simulation data flowchart.
Published 2025“…Hardware-in-the-loop (HIL) validation confirms the algorithm’s robustness under extreme conditions, with lateral stability metrics maintained within safety thresholds.…”
-
11
Hyperparameter Configurations in PPO Training.
Published 2025“…Hardware-in-the-loop (HIL) validation confirms the algorithm’s robustness under extreme conditions, with lateral stability metrics maintained within safety thresholds.…”
-
12
Main parameters of steering system.
Published 2025“…Hardware-in-the-loop (HIL) validation confirms the algorithm’s robustness under extreme conditions, with lateral stability metrics maintained within safety thresholds.…”
-
13
Co-simulation architecture.
Published 2025“…Hardware-in-the-loop (HIL) validation confirms the algorithm’s robustness under extreme conditions, with lateral stability metrics maintained within safety thresholds.…”
-
14
Overall framework diagram of the study.
Published 2025“…Hardware-in-the-loop (HIL) validation confirms the algorithm’s robustness under extreme conditions, with lateral stability metrics maintained within safety thresholds.…”
-
15
Vehicle parameters.
Published 2025“…Hardware-in-the-loop (HIL) validation confirms the algorithm’s robustness under extreme conditions, with lateral stability metrics maintained within safety thresholds.…”
-
16
-
17
GridScopeRodents: High-Resolution Global Typical Rodents Distribution Projections from 2021 to 2100 under Diverse SSP-RCP Scenarios
Published 2025“…Using occurrence data and environmental variable, we employ the Maximum Entropy (MaxEnt) algorithm within the species distribution modeling (SDM) framework to estimate occurrence probability at a spatial resolution of 1/12° (~10 km). …”
-
18
<b>AI for imaging plant stress in invasive species </b>(dataset from the article https://doi.org/10.1093/aob/mcaf043)
Published 2025“…<p dir="ltr">This dataset contains the data used in the article <a href="https://academic.oup.com/aob/advance-article/doi/10.1093/aob/mcaf043/8074229" rel="noreferrer" target="_blank">"Machine Learning and digital Imaging for Spatiotemporal Monitoring of Stress Dynamics in the clonal plant Carpobrotus edulis: Uncovering a Functional Mosaic</a>", which includes the complete set of collected leaf images, image features (predictors) and response variables used to train machine learning regression algorithms.…”
-
19
Brain-in-the-Loop Learning for Intelligent Vehicle Decision-Making
Published 2025“…To achieve policy learning within limited BiTL training periods, we add two modification features to the proposed algorithm based on TD3. …”
-
20
A paired dataset of multi-modal MRI at 3 Tesla and 7 Tesla with manual hippocampal subfield segmentations on 7T T2-weighted images
Published 2024“…This dataset is designed to support the development and evaluation of both 3T-to-7T MR image synthesis models and automated hippocampal segmentation algorithms on 3T images. …”