Search alternatives:
path optimization » whale optimization (Expand Search), based optimization (Expand Search), _ optimization (Expand Search)
values swarm » values were (Expand Search), values near (Expand Search), values serr (Expand Search)
class path » class data (Expand Search)
path optimization » whale optimization (Expand Search), based optimization (Expand Search), _ optimization (Expand Search)
values swarm » values were (Expand Search), values near (Expand Search), values serr (Expand Search)
class path » class data (Expand Search)
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DataSheet1_Quantum-inspired optimization for wavelength assignment.PDF
Published 2023“…Playing a central role in modern telecommunications, this problem belongs to NP-complete class for a general case so that obtaining optimal solutions for industry-relevant cases is exponentially hard. …”
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PathOlOgics_RBCs Python Scripts.zip
Published 2023“…</p><p dir="ltr">In terms of classification, a second algorithm was developed and employed to preliminary sort or group the individual cells (after excluding the overlapping cells manually) into different categories using five geometric measurements applied to the extracted contour from each binary image mask (see PathOlOgics_script_2; preliminary shape measurements). …”
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Thesis-RAMIS-Figs_Slides
Published 2024“…<br><br>Finally, although the developed concepts, ideas and algorithms have been developed for inverse problems in geostatistics, the results are applicable to a wide range of disciplines where similar sampling problems need to be faced, included but not limited to design of communication networks, optimal integration and communication of swarms of robots and drones, remote sensing.…”
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GSE96058 information.
Published 2024“…Subsequently, feature selection was conducted using ANOVA and binary Particle Swarm Optimization (PSO). During the analysis phase, the discriminative power of the selected features was evaluated using machine learning classification algorithms. …”
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The performance of classifiers.
Published 2024“…Subsequently, feature selection was conducted using ANOVA and binary Particle Swarm Optimization (PSO). During the analysis phase, the discriminative power of the selected features was evaluated using machine learning classification algorithms. …”