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algorithm python » algorithm within (Expand Search), algorithms within (Expand Search)
python function » protein function (Expand Search)
algorithm from » algorithm flow (Expand Search)
algorithm both » algorithm blood (Expand Search), algorithm b (Expand Search), algorithm etc (Expand Search)
from function » from functional (Expand Search), fc function (Expand Search)
both function » body function (Expand Search), growth function (Expand Search), beach function (Expand Search)
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141
GSEA analysis.
Published 2025“…The characteristics of the immune microenvironment were assessed using the CIBERSORT R package. Additionally, both the ssGSEA algorithm and the CIBERSORT algorithm were utilized to evaluate changes and effects in immunological characteristics during gastric cancer pathogenesis.…”
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142
Baseline data table.
Published 2025“…The characteristics of the immune microenvironment were assessed using the CIBERSORT R package. Additionally, both the ssGSEA algorithm and the CIBERSORT algorithm were utilized to evaluate changes and effects in immunological characteristics during gastric cancer pathogenesis.…”
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143
KEGG analysis.
Published 2025“…The characteristics of the immune microenvironment were assessed using the CIBERSORT R package. Additionally, both the ssGSEA algorithm and the CIBERSORT algorithm were utilized to evaluate changes and effects in immunological characteristics during gastric cancer pathogenesis.…”
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144
Analysis process.
Published 2025“…The characteristics of the immune microenvironment were assessed using the CIBERSORT R package. Additionally, both the ssGSEA algorithm and the CIBERSORT algorithm were utilized to evaluate changes and effects in immunological characteristics during gastric cancer pathogenesis.…”
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145
DMTD algorithm.
Published 2025“…On the basis of EITO<sub>E</sub>, we propose EITO<sub>P</sub> algorithm using the PPO algorithm to optimize multiple objectives by designing reinforcement learning strategies, rewards, and value functions. …”
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146
Training algorithm flow.
Published 2024“…<div><p>In daily life, two common algorithms are used for collecting medical disease data: data integration of medical institutions and questionnaires. …”
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147
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148
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149
Convergence factor <i>α</i> change graph.
Published 2025“…Finally, a novel Levy flight was implemented to promote the diversity of whale distribution. Results from experiments confirm that the enhanced WOA algorithm outperforms the standard WOA algorithm in terms of both fitness value and convergence speed. …”
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150
Model of ELM.
Published 2025“…Finally, a novel Levy flight was implemented to promote the diversity of whale distribution. Results from experiments confirm that the enhanced WOA algorithm outperforms the standard WOA algorithm in terms of both fitness value and convergence speed. …”
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151
Flowchart of KELM parameters optimized by EAWOA.
Published 2025“…Finally, a novel Levy flight was implemented to promote the diversity of whale distribution. Results from experiments confirm that the enhanced WOA algorithm outperforms the standard WOA algorithm in terms of both fitness value and convergence speed. …”
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152
The flowchart of the proposed EAWOA.
Published 2025“…Finally, a novel Levy flight was implemented to promote the diversity of whale distribution. Results from experiments confirm that the enhanced WOA algorithm outperforms the standard WOA algorithm in terms of both fitness value and convergence speed. …”
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153
Business priorities.
Published 2025“…Based on a comprehensive assessment of service transmission reliability and time costs, a route satisfaction evaluation function model has been developed. Utilizing this model, an enhanced Risk-Time Ant Colony Optimization (RT-ACO) routing algorithm is proposed, which builds upon the traditional ant colony algorithm. …”
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154
Topology of 14-node communication network.
Published 2025“…Based on a comprehensive assessment of service transmission reliability and time costs, a route satisfaction evaluation function model has been developed. Utilizing this model, an enhanced Risk-Time Ant Colony Optimization (RT-ACO) routing algorithm is proposed, which builds upon the traditional ant colony algorithm. …”
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155
Routing policy based on path satisfaction.
Published 2025“…Based on a comprehensive assessment of service transmission reliability and time costs, a route satisfaction evaluation function model has been developed. Utilizing this model, an enhanced Risk-Time Ant Colony Optimization (RT-ACO) routing algorithm is proposed, which builds upon the traditional ant colony algorithm. …”
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156
Changes of risk value under different parameters.
Published 2025“…Based on a comprehensive assessment of service transmission reliability and time costs, a route satisfaction evaluation function model has been developed. Utilizing this model, an enhanced Risk-Time Ant Colony Optimization (RT-ACO) routing algorithm is proposed, which builds upon the traditional ant colony algorithm. …”
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157
Performance of active and standby paths.
Published 2025“…Based on a comprehensive assessment of service transmission reliability and time costs, a route satisfaction evaluation function model has been developed. Utilizing this model, an enhanced Risk-Time Ant Colony Optimization (RT-ACO) routing algorithm is proposed, which builds upon the traditional ant colony algorithm. …”
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158
DATA.
Published 2025“…Based on a comprehensive assessment of service transmission reliability and time costs, a route satisfaction evaluation function model has been developed. Utilizing this model, an enhanced Risk-Time Ant Colony Optimization (RT-ACO) routing algorithm is proposed, which builds upon the traditional ant colony algorithm. …”
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159
Completion times for different algorithms.
Published 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. The effectiveness of the proposed method is then verified on both the physical work cell for riveting and welding and its digital twin platform, and it is compared with other baseline multi-agent reinforcement learning methods (MAPPO, MADDPG, and MASAC). …”
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160
The average cumulative reward of algorithms.
Published 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. The effectiveness of the proposed method is then verified on both the physical work cell for riveting and welding and its digital twin platform, and it is compared with other baseline multi-agent reinforcement learning methods (MAPPO, MADDPG, and MASAC). …”