Search alternatives:
process optimization » model optimization (Expand Search)
codon optimization » wolf optimization (Expand Search)
simple process » single process (Expand Search), complex process (Expand Search), sample processing (Expand Search)
final simple » final sample (Expand Search), final time (Expand Search), via simple (Expand Search)
process optimization » model optimization (Expand Search)
codon optimization » wolf optimization (Expand Search)
simple process » single process (Expand Search), complex process (Expand Search), sample processing (Expand Search)
final simple » final sample (Expand Search), final time (Expand Search), via simple (Expand Search)
-
1
-
2
Simulating Stretch-Induced Crystallization of Polyethylene Films: Strain Rate and Temperature Effect on the Kinetics and Morphology
Published 2024“…A well-known process used to produce recyclable polymer films by stretching is machine direction orientation (MDO). …”
-
3
Loss profile of different fusion algorithms.
Published 2024“…To further improve the communication quality and system processing efficiency, this study combines two different neural network algorithms to optimize the traditional signal automatic modulation classification method. …”
-
4
Nomenclature table.
Published 2024“…The wavelet reconstruction algorithm can simulate all kinds of fast changes in the actual working process more accurately and compress irrelevant information while retaining key signal features, so as to optimize the simulation performance of the model. …”
-
5
Homomorphic binary tree.
Published 2024“…The wavelet reconstruction algorithm can simulate all kinds of fast changes in the actual working process more accurately and compress irrelevant information while retaining key signal features, so as to optimize the simulation performance of the model. …”
-
6
Time taken to simulate running 30 switch cycles.
Published 2024“…The wavelet reconstruction algorithm can simulate all kinds of fast changes in the actual working process more accurately and compress irrelevant information while retaining key signal features, so as to optimize the simulation performance of the model. …”
-
7
Dataset.
Published 2025“…We provide detailed theoretical derivations of the resulting optimization problems of DGRL and KDGRL. Meanwhile, we design two simple and tractable parameter estimation procedures based on cross-validation technique to speed up the model selection processes for DGRL and KDGRL. …”
-
8
-
9
Skeletal_ Muscle_MRI_Registration
Published 2020“…<p><b>MSKregPy</b> is a collection of algorithms and GUI for muscolo-skeletal image processing and registration.…”
-
10
Accuracy and reliability of the fitted curves.
Published 2025“…Then, this model was coupled with the Pareto Envelope-based Selection Algorithm-II (PESA-II) to identify the optimal channels’ characteristics and generate a range of non-dominated solutions that balance implementation costs, system resilience (measured by the Simple Urban Flood Resilience Index, SUFRI), and overflow. …”
-
11
Flowchart of the proposed framework.
Published 2025“…Then, this model was coupled with the Pareto Envelope-based Selection Algorithm-II (PESA-II) to identify the optimal channels’ characteristics and generate a range of non-dominated solutions that balance implementation costs, system resilience (measured by the Simple Urban Flood Resilience Index, SUFRI), and overflow. …”
-
12
Configuration.
Published 2024“…To further improve the communication quality and system processing efficiency, this study combines two different neural network algorithms to optimize the traditional signal automatic modulation classification method. …”
-
13
Diagram of CNN-SRU network structure.
Published 2024“…To further improve the communication quality and system processing efficiency, this study combines two different neural network algorithms to optimize the traditional signal automatic modulation classification method. …”
-
14
SRU neuron structure.
Published 2024“…To further improve the communication quality and system processing efficiency, this study combines two different neural network algorithms to optimize the traditional signal automatic modulation classification method. …”
-
15
CPS network structure.
Published 2024“…To further improve the communication quality and system processing efficiency, this study combines two different neural network algorithms to optimize the traditional signal automatic modulation classification method. …”
-
16
Table of experimental data sets.
Published 2024“…To further improve the communication quality and system processing efficiency, this study combines two different neural network algorithms to optimize the traditional signal automatic modulation classification method. …”
-
17
Single SRU network structure.
Published 2024“…To further improve the communication quality and system processing efficiency, this study combines two different neural network algorithms to optimize the traditional signal automatic modulation classification method. …”
-
18
Structure of a single CNN.
Published 2024“…To further improve the communication quality and system processing efficiency, this study combines two different neural network algorithms to optimize the traditional signal automatic modulation classification method. …”
-
19
Structure of LSTM neuron.
Published 2024“…To further improve the communication quality and system processing efficiency, this study combines two different neural network algorithms to optimize the traditional signal automatic modulation classification method. …”
-
20
SRU-CNN network structure diagram.
Published 2024“…To further improve the communication quality and system processing efficiency, this study combines two different neural network algorithms to optimize the traditional signal automatic modulation classification method. …”