Solving the multi-commodity flow problem using an evolutionary routing algorithm in a computer network environment حسب Noel Farrugia (19945083)

"…<p dir="ltr">The continued increase in Internet traffic requires that routing algorithms make the best use of all available network resources. …"

Comparison of input image reconstruction results between the dynamic routing algorithm and our method on the MNIST, F-MNIST, and K-MNIST datasets. حسب Hailei Yuan (21608693)

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Comparison of F1 score, Precision, Recall, and AUC for different advanced capsule network routing algorithms (baseline) and their improvements with our method across various datasets. حسب Hailei Yuan (21608693)

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Experimental results comparing the classification accuracy (Acc., %) and standard deviation (Std.) of the proposed method with the original dynamic routing algorithm. CNN refers to a convolutional neural network with a parameter count comparable to the original dynamic routing capsule network. CapsNet-DR refers to the capsule network using the standard dynamic routing algorithm, CapsNet-CRI denotes the dynamic routing algorithm with inverse initialization of the coupling coefficients, DC-CapsNet-DR applies the group strategy with standard dynamic routing, and DC-CapsNet (Ours) is our full method. حسب Hailei Yuan (21608693)

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MTVRP.ipynb حسب Brayan Steven Perdomo Cardenas (20553410)

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Experimental results comparing the classification accuracy (Acc., %) and standard deviation (Std.) of advanced capsule network routing algorithms with the proposed DC-CapsNet method.... حسب Hailei Yuan (21608693)

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Evaluation of the impact of different routing iterations on the classification accuracy (Acc., %) and standard deviation (Std.) of the proposed DC-CapsNet across various datasets.... حسب Hailei Yuan (21608693)

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Experimental results evaluating the impact of different group numbers in the proposed DC-CapsNet. The results demonstrate how varying the number of groups affects classification ac... حسب Hailei Yuan (21608693)

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Comparison of runtime (seconds per epoch), number of parameters (M), and memory consumption (MB) for CapsNet-DR and DC-CapsNet (Ours) on different datasets. حسب Hailei Yuan (21608693)

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The architecture of DC-CapsNet consists of four main components: a convolutional layer, a primary capsule layer, a divide-and-conquer module, and inter-group routing. حسب Hailei Yuan (21608693)

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Comparison of the original images and visualizations from different capsule groups. حسب Hailei Yuan (21608693)

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Comparison of F1 score, Precision, Recall, AUC among CNN, CapsNet-DR and DC-CapsNet across different datasets. حسب Hailei Yuan (21608693)

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Illustration of coupling coefficient initialization and capsule aggregation methods. حسب Hailei Yuan (21608693)

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Changes of the delay of the two methods in iteration. حسب Yang Yu (4292)

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Business priorities. حسب Yang Yu (4292)

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The relationship between the satisfaction and the number of transactions under the two methods. حسب Yang Yu (4292)

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Ant colony algorithm function and parameter explanation. حسب Yang Yu (4292)

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Routing reconstruction policy with service priority. حسب Yang Yu (4292)

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Topology of 14-node communication network. حسب Yang Yu (4292)

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Routing policy based on path satisfaction. حسب Yang Yu (4292)

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