Search alternatives:
fitting algorithm » finding algorithm (Expand Search), filtering algorithm (Expand Search), twisting algorithm (Expand Search)
method algorithm » network algorithm (Expand Search), means algorithm (Expand Search), mean algorithm (Expand Search)
using algorithm » using algorithms (Expand Search), routing algorithm (Expand Search), fusion algorithm (Expand Search)
data fitting » data settings (Expand Search), data mining (Expand Search)
fitting algorithm » finding algorithm (Expand Search), filtering algorithm (Expand Search), twisting algorithm (Expand Search)
method algorithm » network algorithm (Expand Search), means algorithm (Expand Search), mean algorithm (Expand Search)
using algorithm » using algorithms (Expand Search), routing algorithm (Expand Search), fusion algorithm (Expand Search)
data fitting » data settings (Expand Search), data mining (Expand Search)
-
1
Algorithmic experimental parameter design.
Published 2024“…The results of numerical simulations and sea trial experimental data indicate that the use of subarrays comprising 5 and 3 array elements, respectively, is sufficient to effectively estimate 12 source angles. …”
-
2
Spatial spectrum estimation for three algorithms.
Published 2024“…The results of numerical simulations and sea trial experimental data indicate that the use of subarrays comprising 5 and 3 array elements, respectively, is sufficient to effectively estimate 12 source angles. …”
-
3
Coprime array with interpolated array elements.
Published 2024“…The results of numerical simulations and sea trial experimental data indicate that the use of subarrays comprising 5 and 3 array elements, respectively, is sufficient to effectively estimate 12 source angles. …”
-
4
Mean and root mean square errors of DOA estimate.
Published 2024“…The results of numerical simulations and sea trial experimental data indicate that the use of subarrays comprising 5 and 3 array elements, respectively, is sufficient to effectively estimate 12 source angles. …”
-
5
Schematic diagram of maritime array arming.
Published 2024“…The results of numerical simulations and sea trial experimental data indicate that the use of subarrays comprising 5 and 3 array elements, respectively, is sufficient to effectively estimate 12 source angles. …”
-
6
Variation of RMSE with the number of snapshots.
Published 2024“…The results of numerical simulations and sea trial experimental data indicate that the use of subarrays comprising 5 and 3 array elements, respectively, is sufficient to effectively estimate 12 source angles. …”
-
7
Velocity of sound profile.
Published 2024“…The results of numerical simulations and sea trial experimental data indicate that the use of subarrays comprising 5 and 3 array elements, respectively, is sufficient to effectively estimate 12 source angles. …”
-
8
Variation of RMSE with input SNR.
Published 2024“…The results of numerical simulations and sea trial experimental data indicate that the use of subarrays comprising 5 and 3 array elements, respectively, is sufficient to effectively estimate 12 source angles. …”
-
9
Coprime array.
Published 2024“…The results of numerical simulations and sea trial experimental data indicate that the use of subarrays comprising 5 and 3 array elements, respectively, is sufficient to effectively estimate 12 source angles. …”
-
10
Variation of RMSE with different grid spacing.
Published 2024“…The results of numerical simulations and sea trial experimental data indicate that the use of subarrays comprising 5 and 3 array elements, respectively, is sufficient to effectively estimate 12 source angles. …”
-
11
Spatial power spectrum of compact sound source.
Published 2024“…The results of numerical simulations and sea trial experimental data indicate that the use of subarrays comprising 5 and 3 array elements, respectively, is sufficient to effectively estimate 12 source angles. …”
-
12
-
13
Table 1_In Vitro biomechanical study of meniscal properties in patients with severe knee osteoarthritis.xlsx
Published 2025“…Quantifying the biomechanical properties of the meniscus is essential for understanding its role in knee joint function and pathology.</p>Methods<p>This study aimed to determine the biomechanical properties of the meniscus in patients with severe KOA using experimental mechanical testing and an inverse finite element analysis (iFEA) model. …”
-
14
Table 2_In Vitro biomechanical study of meniscal properties in patients with severe knee osteoarthritis.xlsx
Published 2025“…Quantifying the biomechanical properties of the meniscus is essential for understanding its role in knee joint function and pathology.</p>Methods<p>This study aimed to determine the biomechanical properties of the meniscus in patients with severe KOA using experimental mechanical testing and an inverse finite element analysis (iFEA) model. …”
-
15
DataSheet1_Enhancing slope stability prediction through integrated PCA-SSA-SVM modeling: a case study of LongLian expressway.docx
Published 2024“…Traditional slope stability analysis methods, such as the limit equilibrium method, limit analysis method, and finite element method, often face limitations due to computational complexity and the need for extensive soil property data. …”
-
16
An optional formula for calculating crustal thickness using Sr/Y ratio and its application to the southeastern margin of the Central Asian Orogenic Belt
Published 2025“…Global lower crust-derived magmatic rock (younger than 23 Ma) data from diverse geological settings were selected and filtered using key geochemical criteria, alternating and iteratively using K-means clustering algorithm and improved Thompson tau method to exclude outliers. …”
-
17
<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.…”