Search alternatives:
modeling algorithm » making algorithm (Expand Search)
method algorithm » network algorithm (Expand Search), means algorithm (Expand Search), mean algorithm (Expand Search)
elements method » element method (Expand Search)
first algorithm » forest algorithm (Expand Search), forest algorithms (Expand Search), best algorithm (Expand Search)
data modeling » data modelling (Expand Search), data models (Expand Search)
data first » data fit (Expand Search), data figs (Expand Search)
modeling algorithm » making algorithm (Expand Search)
method algorithm » network algorithm (Expand Search), means algorithm (Expand Search), mean algorithm (Expand Search)
elements method » element method (Expand Search)
first algorithm » forest algorithm (Expand Search), forest algorithms (Expand Search), best algorithm (Expand Search)
data modeling » data modelling (Expand Search), data models (Expand Search)
data first » data fit (Expand Search), data figs (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
The run time for each algorithm in seconds.
Published 2025“…The goal of this paper is to examine several extensions to KGR/GPoG, with the aim of generalising them a wider variety of data scenarios. The first extension we consider is the case of graph signals that have only been partially recorded, meaning a subset of their elements is missing at observation time. …”
-
3
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. …”
-
4
-
5
Raw performance data for the first algorithm shown in Fig 9.
Published 2025“…<p>Raw performance data for the first algorithm shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0328223#pone.0328223.g009" target="_blank">Fig 9</a>.…”
-
6
Comparison of the EODA algorithm with existing algorithms in terms of recall.
Published 2025Subjects: -
7
Comparison of the EODA algorithm with existing algorithms in terms of precision.
Published 2025Subjects: -
8
Comparison of the EODA algorithm with existing algorithms in terms of F1-Score.
Published 2025Subjects: -
9
-
10
-
11
-
12
-
13
-
14
-
15
-
16
-
17
-
18
-
19
Scatter diagram of different principal elements.
Published 2025“…<div><p>A fault diagnosis method for oil immersed transformers based on principal component analysis and SSA LightGBM is proposed to address the problem of low diagnostic accuracy caused by the complexity of current oil immersed transformer faults. Firstly, data on dissolved gases in oil is collected, and a 17 dimensional fault feature matrix is constructed using the uncoded ratio method. …”
-
20