In order to address the issue of low segmentation accuracy in the weak flame region of waste incineration flame images and the potential loss of texture details at the flame edge, this study proposes an algorithm for ...
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This study explores polynomial Markov positive fuzzy systems, formulating controllers for these systems by examining the prerequisites for positivity and stochastic stability. Initially, polynomials are incorporated i...
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As the popularity and dependence on the Internet increase,DDoS(distributed denial of service)attacks seriously threaten network *** accurately distinguishing between different types of DDoS attacks,targeted defense st...
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As the popularity and dependence on the Internet increase,DDoS(distributed denial of service)attacks seriously threaten network *** accurately distinguishing between different types of DDoS attacks,targeted defense strategies can be formulated,significantly improving network protection *** attacks usually manifest as an abnormal increase in network traffic,and their diverse types of attacks,along with a severe data imbalance,make it difficult for traditional classification methods to effectively identify a small number of attack *** solve this problem,this paper proposes a DDoS recognition method CVWGG(Conditional Variational Autoencoder-Wasserstein Generative Adversarial Network-gradient penalty-Gated Recurrent Unit)for unbalanced data,which generates less noisy data and high data quality compared with existing *** mainly includes unbalanced data processing for CVWG,feature extraction,and *** uses the CVAE(Conditional Variational Autoencoder)to improve the WGAN(Wasserstein Generative Adversarial Network)and introduces a GP(gradient penalty)term to design the loss function to generate balanced data,which enhances the learning ability and stability of the ***,the GRU(Gated Recurrent Units)are used to capture the temporal features and patterns of the ***,the logsoftmax function is used to differentiate DDoS attack *** PyCharm and Python 3.10 for programming and evaluating performance with metrics such as accuracy and precision,the results show that the method achieved accuracy rates of 96.0%and 97.3%on two datasets,***,comparison and ablation experiment results demonstrate that CVWGG effectively mitigates the imbalance between DDoS attack categories,significantly improves the classification accuracy of different types of attacks and provides a valuable reference for network security defense.
The relationship between users and items,which cannot be recovered by traditional techniques,can be extracted by the recommendation algorithm based on the graph convolution *** current simple linear combination of the...
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The relationship between users and items,which cannot be recovered by traditional techniques,can be extracted by the recommendation algorithm based on the graph convolution *** current simple linear combination of these algorithms may not be sufficient to extract the complex structure of user interaction *** paper presents a new approach to address such issues,utilizing the graph convolution network to extract association *** proposed approach mainly includes three modules:Embedding layer,forward propagation layer,and score prediction *** embedding layer models users and items according to their interaction information and generates initial feature vectors as input for the forward propagation *** forward propagation layer designs two parallel graph convolution networks with self-connections,which extract higher-order association relevance from users and items separately by multi-layer graph ***,the forward propagation layer integrates the attention factor to assign different weights among the hop neighbors of the graph convolution network fusion,capturing more comprehensive association relevance between users and items as input for the score prediction *** score prediction layer introduces MLP(multi-layer perceptron)to conduct non-linear feature interaction between users and items,***,the prediction score of users to items is *** recall rate and normalized discounted cumulative gain were used as evaluation *** proposed approach effectively integrates higher-order information in user entries,and experimental analysis demonstrates its superiority over the existing algorithms.
Smart grid networks play a key role in making electric power infrastructure more efficient and ensuring reliable energy distribution. However, the interconnected communication devices in these networks expose the syst...
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Security incidents in smart contracts still occur frequently, as the underlying code is often vulnerable to attacks. However, traditional methods to detect vulnerabilities in smart contracts are limited by certain rig...
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User preferences play an important role in intelligent services, smart recommendations, and so on. Unfortunately, user preferences are dynamic and always evolving. How to proactively perceive users’ preferences evolu...
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Considering the low accuracy of recommendation results of current collaborative filtering algorithms caused by data sparsity, this paper proposes a weighted Slope One collaborative filtering algorithm for improved use...
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The AC-DC Energy Nodes (ADENs) concept offers a transformative approach to modernizing power grids, particularly in the context of supergrids. By centralizing power flows from diverse renewable energy sources, such as...
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This paper addresses the challenge of differentiable rendering, focusing on a novel implementation designed to integrate 3D objects seamlessly into reconstructed 3D environments, thereby creating entirely new perspect...
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