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Journal articles on the topic 'Network method'

Author: Grafiati

Published: 28 May 2022

Last updated: 30 July 2025

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1

Haviluddin and Rayner Alfred. "Forecasting Network Activities Using ARIMA Method." Journal of Advances in Computer Networks 2, no. 3 (2014): 173–77. http://dx.doi.org/10.7763/jacn.2014.v2.106.

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Armitage, Neil. "The Biographical Network Method." Sociological Research Online 21, no. 2 (2016): 165–79. http://dx.doi.org/10.5153/sro.3827.

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This article introduces a network visualization method that enables a thorough analysis of the link between life history and social networks. Network visualizations are generally static, and as such they tend to disguise rather than uncover change and continuity within networks, and the influence that certain events may have on someone's sociability. The Biographical Network (BN) is a mixed method approach combining life story interviews with formal SNA that attempts to overcome the consequences of this lack of dynamism in network visualizations. In the first part of the article the underpinni

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Yakasova, Natalya. "Holographic method of neural network design." E3S Web of Conferences 419 (2023): 02026. http://dx.doi.org/10.1051/e3sconf/202341902026.

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The paper presents a method for solving the problem of changing a full-connected neural network of direct propagation with a sigmoid activation function in the conditions of the emergence of a new class, with the ability to preserve the network to recognize already known classes and to classify objects of a new class. Such conditions generate a new neural network, which is trained on examples of all classes, including the new class. The learning process takes a long time and requires the selection of several parameters. The emergence of a new class in natural neural networks does not cause a t

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Li, Keping, Shuang Gu, and Dongyang Yan. "A Link Prediction Method Based on Neural Networks." Applied Sciences 11, no. 11 (2021): 5186. http://dx.doi.org/10.3390/app11115186.

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Link prediction to optimize network performance is of great significance in network evolution. Because of the complexity of network systems and the uncertainty of network evolution, it faces many challenges. This paper proposes a new link prediction method based on neural networks trained on scale-free networks as input data, and optimized networks trained by link prediction models as output data. In order to solve the influence of the generalization of the neural network on the experiments, a greedy link pruning strategy is applied. We consider network efficiency and the proposed global netwo

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NEZNÍK, Dominik, and Ľubomír DOBOŠ. "CHANNEL ALLOCATION FOR WIRELESS NETWORKS BASED ON INTELLIGENT METHOD." Acta Electrotechnica et Informatica 20, no. 4 (2021): 32–37. http://dx.doi.org/10.15546/aeei-2020-0023.

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In this paper, will be presented actual research of the intelligent channel allocation. The intelligent channel allocation is based on combination of fuzzy logic method and game theory attributes to increase quality of link in network. The channel allocations will become an important phenomenon in different types of networks such as 5G technology, wireless networks (IEEE 802.11xx), Z-Wave, LoRa, 3G, 4G, etc. In the near future, new network technologies, Internet of Things (IoT) and Smart Cities will need to have intelligent channel allocation to prevent interference on the channels used for da

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Hong-Rong Jing, Hong-Rong Jing, Guo-Jun Lin Hong-Rong Jing, Zhong-Ling Liu Guo-Jun Lin, et al. "Face Recognition Method Based on Lightweight Network SE-ShuffleNet V2." 電腦學刊 34, no. 4 (2023): 015–24. http://dx.doi.org/10.53106/199115992023083404002.

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<p>We develop a more efficient lightweight network based on SE-ShuffleNet V2 to address the issues of large parameter sizes and sluggish feature extraction rates in large networks in the field of face recognition.&nbsp;First, to increase the network&rsquo;s accuracy and inference speed, the ReLU activation function of the original ShuffleNet V2 basic unit is swapped out for a segmented linear activation function. Second, the SE attention mechanism is added to the lightweight network ShuffleNet V2, which may improve the effective feature weights and decrease the invalid feature we

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Ma, Lili, Jiangping Liu, and Jidong Luo. "Method of Wireless Sensor Network Data Fusion." International Journal of Online Engineering (iJOE) 13, no. 09 (2017): 114. http://dx.doi.org/10.3991/ijoe.v13i09.7589.

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<p style="margin: 1em 0px;"><span lang="EN-US"><span style="font-family: 宋体; font-size: medium;">In order to better deal with large data information in computer networks, a large data fusion method based on wireless sensor networks is designed. Based on the analysis of the structure and learning algorithm of RBF neural networks, a heterogeneous RBF neural network information fusion algorithm in wireless sensor networks is presented. The effectiveness of information fusion processing methods is tested by RBF information fusion algorithm. The proposed algorithm is applied to he

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Dong, Cheng Gen, Jin Pei Wu, and Qi Shan Zhang. "One Fault Diagnosis Method of Telecommunications Network." Advanced Materials Research 301-303 (July 2011): 1172–77. http://dx.doi.org/10.4028/www.scientific.net/amr.301-303.1172.

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Telecommunications network fault location process of the root cause is the fault diagnosis process, there are mature products in general is the use of rule-based approach, rule-based approach is not suitable because of its inherent defects in the application of large-scale telecommunications networks, Thought about the uncertainty and incomplete of telecommunications networks events in nature, this article applied Bayesian network method to solve the information uncertainty and incomplete of telecommunications networks events, taking on the Bayesian reasoning method, proposed three optimizatio

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Peng, Yun, and Zonglin Zhou. "A neural network learning method for belief networks." International Journal of Intelligent Systems 11, no. 11 (1998): 893–915. http://dx.doi.org/10.1002/(sici)1098-111x(199611)11:11<893::aid-int3>3.0.co;2-u.

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Zhang, Hu, Jingjing Zhou, Ru Li, and Yue Fan. "Network representation learning method embedding linear and nonlinear network structures." Semantic Web 13, no. 3 (2022): 511–26. http://dx.doi.org/10.3233/sw-212968.

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With the rapid development of neural networks, much attention has been focused on network embedding for complex network data, which aims to learn low-dimensional embedding of nodes in the network and how to effectively apply learned network representations to various graph-based analytical tasks. Two typical models exist namely the shallow random walk network representation method and deep learning models such as graph convolution networks (GCNs). The former one can be used to capture the linear structure of the network using depth-first search (DFS) and width-first search (BFS), whereas Hiera

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Wang, Chen, Chengyi Zeng, Hongfu Liu, and Jing Chen. "Adversarial Hiding Deception Strategy and Network Optimization Method for Heterogeneous Network Defense." Electronics 10, no. 21 (2021): 2614. http://dx.doi.org/10.3390/electronics10212614.

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Heterogeneous networks are powerful tools for describing different types of entities and relationships and are more relevant models of complex networks. The study of heterogeneous network defense is of great practical significance for protecting useful networks such as military combat networks and critical infrastructure networks. However, a large amount of current research on complex network defense focuses on homogeneous networks under complete information conditions, which often ignore the real conditions such as incomplete information and heterogeneous networks. In this paper, we propose f

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Wang, Chun-Feng, and Kui Liu. "A Novel Hybrid Method for Learning Bayesian Network." Journal of Computers 10, no. 2 (2015): 130–37. http://dx.doi.org/10.17706/jcp.10.2.130-137.

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Kumar S, Raj. "Network-on-Chip Architecture Based on Cluster Method." International Journal of Scientific Engineering and Research 3, no. 3 (2015): 61–65. https://doi.org/10.70729/ijser1512.

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Mohammad, Nawar. "DEVELOPMENT OF WIRELESS SENSOR NETWORKS EFFICIENT CLUSTERIZATION METHOD." SYNCHROINFO JOURNAL 10, no. 1 (2024): 32–38. http://dx.doi.org/10.36724/2664-066x-2024-10-1-32-38.

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Wireless sensor networks are a critical element of the Internet of Things and are widely used in various fields. Effective clustering is key to energy efficiency and network stability in wireless sensor networks. Optimize the density of clusters, their number and size to increase the stability and service life of the network – It is one of the tasks of clustering wireless sensor networks. Another problem – effectively organize the network topology in order to balance the load and extend the network lifetime. Clustering has proven to be an effective approach for organizing a network into a cohe

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Dzwigol, Henryk. "Network Analysis as a Research Method." E3S Web of Conferences 456 (2023): 03001. http://dx.doi.org/10.1051/e3sconf/202345603001.

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Network analysis has emerged as a powerful research approach, breaking down disciplinary barriers to examine intricate relationships across various fields. By depicting entities as nodes and relationships as edges, this method constructs networks that unveil patterns and dynamics. This study delves into the fundamental principles of network analysis, emphasizing its effectiveness in revealing hidden patterns, pinpointing influential factors, and understanding the flow of information. It facilitates examination at both micro and macro levels, with key components such as centrality measures and

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Ruan, Kun, Shun Zhao, Xueqin Jiang, et al. "A 3D Fluorescence Classification and Component Prediction Method Based on VGG Convolutional Neural Network and PARAFAC Analysis Method." Applied Sciences 12, no. 10 (2022): 4886. http://dx.doi.org/10.3390/app12104886.

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Three-dimensional fluorescence is currently studied by methods such as parallel factor analysis (PARAFAC), fluorescence regional integration (FRI), and principal component analysis (PCA). There are also many studies combining convolutional neural networks at present, but there is no one method recognized as the most effective among the methods combining convolutional neural networks and 3D fluorescence analysis. Based on this, we took some samples from the actual environment for measuring 3D fluorescence data and obtained a batch of public datasets from the internet species. Firstly, we prepro

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Golubinskiy, Andrey, and Andrey Tolstykh. "Hybrid method of conventional neural network training." Informatics and Automation 20, no. 2 (2021): 463–90. http://dx.doi.org/10.15622/ia.2021.20.2.8.

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The paper proposes a hybrid method for training convolutional neural networks. The method consists of combining second and first-order methods for different elements of the architecture of a convolutional neural network. The hybrid convolution neural network training method allows to achieve significantly better convergence compared to Adam; however, it requires fewer computational operations to implement. Using the proposed method, it is possible to train networks on which learning paralysis occurs when using first-order methods. Moreover, the proposed method could adjust its computational co

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Xianhao Shen, Xianhao Shen, Changhong Zhu Xianhao Shen, Yihao Zang Changhong Zhu, and Shaohua Niu Yihao Zang. "A Method for Detecting Abnormal Data of Network Nodes Based on Convolutional Neural Network." 電腦學刊 33, no. 3 (2022): 049–58. http://dx.doi.org/10.53106/199115992022063303004.

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<p>Abnormal data detection is an important step to ensure the accuracy and reliability of node data in wireless sensor networks. In this paper, a data classification method based on convolutional neural network is proposed to solve the problem of data anomaly detection in wireless sensor networks. First, Normal data and abnormal data generated after injection fault are normalized and mapped to gray image as input data of the convolutional neural network. Then, based on the classical convolution neural network, three new convolutional neural network models are designed by designing the pa

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Madaan, Jyoti, Sunanda Gupta, and Pratima Manihas. "A new method for handoff target network selection." IAES International Journal of Robotics and Automation (IJRA) 8, no. 1 (2019): 36. http://dx.doi.org/10.11591/ijra.v8i1.pp36-43.

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In wireless communications of fourth generation the expectation to assimilate a hypothetically numerous heterogeneous wireless technologies are happened under consideration of a novel step toward worldwide smooth access. The advancement in wireless networks increases the challenges of mobility management as well the challenges of merging a various number of wireless networks. Out of those the main challenge for smooth movement is the accessibility of consistent vertical (intersystem) and horizontal (intra-system) handoff processes. So to improve the quality of service and to provide always bes

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Madaan, Jyoti, Sunanda Gupta, and Pratima Manihas. "A new method for handoff target network selection." IAES International Journal of Robotics and Automation (IJRA) 8, no. 1 (2019): 36–43. https://doi.org/10.11591/ijra.v8i1.pp36-43.

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In wireless communications of fourth generation the expectation to assimilate a hypothetically numerous heterogeneous wireless technologies are happened under consideration of a novel step toward worldwide smooth access. The advancement in wireless networks increases the challenges of mobility management as well the challenges of merging a various number of wireless networks. Out of those the main challenge for smooth movement is the accessibility of consistent vertical (intersystem) and horizontal (intra-system) handoff processes. So to improve the quality of service and to provide always bes

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Xue, Kun, Xiaoxia Han, Jinde Wu, Yadi Shen, Xinying Xu, and Gang Xie. "Community detection based on competitive walking network embedding method." Journal of Statistical Mechanics: Theory and Experiment 2022, no. 9 (2022): 093402. http://dx.doi.org/10.1088/1742-5468/ac8807.

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Abstract Currently, much of the information of the real world is network-structured, and extracting hidden information from network-structured data helps to understand the corresponding systems, but can also be a challenging problem. In recent years, network embedding has been an effective way to extract network information, which represents nodes in complex networks as low-dimensional space vectors, while preserving the properties of the network. Community attributes are an important property of networks, and in most network embedding algorithms, the community structure is usually ignored or

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Su, Shiwei, Yiran You, and Yu Zou. "COMPREHENSIVE METHOD FOR EVALUATION OF MEDIUM- AND LOW-VOLTAGE DISTRIBUTION NETWORK OPERATING STATE." Tekhnichna Elektrodynamika 2020, no. 6 (2020): 47–56. http://dx.doi.org/10.15407/techned2020.06.047.

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With the development of intelligent distribution networks and access to distributed energy, the solving the problem of timely and accurate determination of the operating state of the distribution network is an urgent task. Based on an improved analysis of the principle components of the network and statements of a self-organizing neural network, this article proposes the method to evaluate the operating state of medium- and low-voltage distribution networks. At the first step, the system of evaluating indices of the network is formed by advanced component analysis. The evaluation system is gro

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Levin, Maxim, Anastasia Sevostyanova, Stanislav Nagornov, Irina Kovalenko, and Ekaterina Levina. "METHOD OF CONSTRUCTING A NEURAL NETWORK BASED ON BIOMATERIALS." SCIENCE IN THE CENTRAL RUSSIA, no. 6 (December 27, 2024): 105–13. https://doi.org/10.35887/2305-2538-2024-6-105-113.

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The modern approach to building neural networks evolves and continues to develop in improving the mathematical model of neuron functioning, which leads to new differences from real biological analogues, since a highly simplified model of the basic element (neuron) is used to model modern neural networks. The purpose of this work is to calculate the information capacity of a neural network built on a biological neuron, to provide evidence of the prospects for studying methods for building a neural network using biological neurons. A mathematical description of the main structural elements of a

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Williams, Trenton A., and Dean A. Shepherd. "Mixed Method Social Network Analysis." Organizational Research Methods 20, no. 2 (2016): 268–98. http://dx.doi.org/10.1177/1094428115610807.

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This article outlines a mixed method approach to social network analysis combining techniques of organizational history development, inductive data structuring, and content analysis to offer a novel approach for network data construction and analysis. This approach provides researchers with a number of benefits over traditional sociometric or other interpersonal methodologies including the ability to investigate networks of greater scope, broader access to diverse social actors, reduced informant bias, and increased capability for longitudinal designs. After detailing this approach, we apply t

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Jin, Xi, Nan Guan, Jintao Wang, and Peng Zeng. "Analyzing Multimode Wireless Sensor Networks Using the Network Calculus." Journal of Sensors 2015 (2015): 1–12. http://dx.doi.org/10.1155/2015/851608.

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The network calculus is a powerful tool to analyze the performance of wireless sensor networks. But the original network calculus can only model the single-mode wireless sensor network. In this paper, we combine the original network calculus with the multimode model to analyze the maximum delay bound of the flow of interest in the multimode wireless sensor network. There are two combined methods A-MM and N-MM. The method A-MM models the whole network as a multimode component, and the method N-MM models each node as a multimode component. We prove that the maximum delay bound computed by the me

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Xiaoxuan Ma, Xiaoxuan Ma, Sihan Shan Xiaoxuan Ma, and Dong Sui Sihan Shan. "A Medical Image Segmentation Method Combining Knowledge Distillation and Contrastive Learning." 電腦學刊 35, no. 3 (2024): 363–77. http://dx.doi.org/10.53106/199115992024063503024.

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<p>Recent advances in feature-based knowledge distillation have shown promise in computer vision, yet their direct application to medical image segmentation has been challenging due to the inherent high intra-class variance and class imbalance prevalent in medical images. This paper introduces a novel approach that synergizes knowledge distillation with contrastive learning to enhance the performance of student networks in medical image segmentation. By leveraging importance maps and region affinity graphs, our method encourages the student network to deeply explore the regional feature

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Qi, Shengyuan, Lin Yang, Linru Ma, Shanqing Jiang, and Guang Cheng. "Dual-Network Layered Network: A Method to Improve Reliability, Security, and Network Efficiency in Distributed Heterogeneous Network Transmission." Electronics 13, no. 23 (2024): 4749. https://doi.org/10.3390/electronics13234749.

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This article delves into the routing architecture and reliable transmission service framework of dual-network layered networks, with a focus on analyzing their core design ideas and implementation strategies. In the context of increasing network complexity today, traditional single-network architectures are unable to meet diverse application needs. Therefore, dual-network layered networks, as an innovative solution, are gradually receiving attention from both academia and industry. This article first analyzes the key technical elements in the dual-network layered network architecture, includin

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Shen, Bin, Muwei Zhao, Wei Zhong, and Jieyue He. "An Improved Method for Completely Uncertain Biological Network Alignment." BioMed Research International 2015 (2015): 1–11. http://dx.doi.org/10.1155/2015/253854.

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With the continuous development of biological experiment technology, more and more data related to uncertain biological networks needs to be analyzed. However, most of current alignment methods are designed for the deterministic biological network. Only a few can solve the probabilistic network alignment problem. However, these approaches only use the part of probabilistic data in the original networks allowing only one of the two networks to be probabilistic. To overcome the weakness of current approaches, an improved method called completely probabilistic biological network comparison alignm

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Liu, Kuan, Haiyuan Liu, Dongyan Sun, and Lei Zhang. "Network Inference from Gene Expression Data with Distance Correlation and Network Topology Centrality." Algorithms 14, no. 2 (2021): 61. http://dx.doi.org/10.3390/a14020061.

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The reconstruction of gene regulatory networks based on gene expression data can effectively uncover regulatory relationships between genes and provide a deeper understanding of biological control processes. Non-linear dependence is a common problem in the regulatory mechanisms of gene regulatory networks. Various methods based on information theory have been developed to infer networks. However, the methods have introduced many redundant regulatory relationships in the network inference process. A recent measurement method called distance correlation has, in many cases, shown strong and compu

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Liu, Zhiguo, Xiaoqi Dong, Lin Wang, Jianxin Feng, Chengsheng Pan, and Yunqi Li. "Satellite Network Task Deployment Method Based on SDN and ICN." Sensors 22, no. 14 (2022): 5439. http://dx.doi.org/10.3390/s22145439.

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With the rapid development of 5G and the Internet of Things, satellite networks are emerging as an indispensable part of realizing wide-area coverage. The growth of the constellation of low-orbit satellites makes it possible to deploy edge computing services in satellite networks. This is, however, challenging due to the topological dynamics and limited resources of satellite networks. To improve the performance of edge computing in a satellite network, we propose a satellite network task deployment method based on SDN (software-defined network) and ICN (information-centric network). In this m

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Rahman, Atta-ur, Maqsood Mahmud, Tahir Iqbal, et al. "Network Anomaly Detection in 5G Networks." Mathematical Modelling of Engineering Problems 9, no. 2 (2022): 397–404. http://dx.doi.org/10.18280/mmep.090213.

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On the telecommunications front, 5G is the fifth-generation technology standard for broadband cellular networks, which is a replacement for the 4G networks used by most current phones. Hundreds of businesses, organizations, and governments suffer from cyberattacks that compromise sensitive information in which 5G is one of them. Those breaches of the data would not have occurred if there is a way to detect strange behaviors in a 5G network, and this is what this paper presenting. Network Anomaly Detection (NAD) in 5G is a way to observe the network constantly to detect any unusual behavior. Ho

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Song, Zhuoran, Jianfeng Li, Tao Jiang, and Sichen Lu. "Distribution Network Planning Method considering the Coupling of Transportation Network and Distribution Network." Scalable Computing: Practice and Experience 24, no. 3 (2023): 429–38. http://dx.doi.org/10.12694/scpe.v24i3.2288.

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This paper introduces a novel distribution network planning method that addresses the limitations of conventional approaches. The existing methods primarily focus on optimizing component objectives using reliability analysis, which results in inadequate operational power control performance due to neglecting the coupling degree analysis of distribution network subprojects. To overcome this limitation, the proposed method incorporates the coupling of the traffic and distribution networks into the planning process. The method involves modeling the transportation network and analyzing the couplin

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Kudelya, Viktor N., Valentine E. Gel, and Valeriy V. Vovk. "METHOD OF RAPID ANALYSIS OF STABILITY FUNCTIONING MULTISERVICE COMMUNICATION NETWORK." T-Comm 15, no. 7 (2021): 23–27. http://dx.doi.org/10.36724/2072-8735-2021-15-7-23-27.

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Continuous improvement of the architecture of multi-service communication networks (MCN) is due to the need for networks with a capacity of tens of Tbit/s. Existing communication networks are multi-pole [1,2] and, in this regard, the term “network bandwidth” loses its meaning. Based on this, the term “network performance” is used. Such performance requires the development of methods for complex analysis of network stability and organization of its functioning. Usually, the network stability is considered in two aspects: potential and structural. This article discusses the models of stability a

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Hou, Xiaohui, Lei Huang, and Xuefei Li. "An Effective Method to Evaluate the Scientific Research Projects." Foundations of Computing and Decision Sciences 39, no. 3 (2014): 175–88. http://dx.doi.org/10.2478/fcds-2014-0010.

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Abstract The evaluation of the scientific research projects is an important procedure before the scientific research projects are approved. The BP neural network and linear neural network are adopted to evaluate the scientific research projects in this paper. The evaluation index system with 12 indexes is set up. The basic principle of the neural network is analyzed and then the BP neural network and linear neural network models are constructed and the output error function of the neural networks is introduced. The Matlab software is applied to set the parameters and calculate the neural netwo

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Yang, Yunfeng, and Fengxian Tang. "Network Intrusion Detection Based on Stochastic Neural Networks Method." International Journal of Security and Its Applications 10, no. 8 (2016): 435–46. http://dx.doi.org/10.14257/ijsia.2016.10.8.38.

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Yin, Ying, Li-Xin Ji, Jian-Peng Zhang, and Yu-Long Pei. "DHNE: Network Representation Learning Method for Dynamic Heterogeneous Networks." IEEE Access 7 (2019): 134782–92. http://dx.doi.org/10.1109/access.2019.2942221.

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Wang, Yike, Gaoxia Wang, Ximei Hou, and Fan Yang. "Motif adjacency matrix and spectral clustering of directed weighted networks." AIMS Mathematics 8, no. 6 (2023): 13797–814. http://dx.doi.org/10.3934/math.2023706.

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<abstract> <p>In the spectral clustering methods, different from the network division based on edges, some research has begun to divide the network based on network motifs; the corresponding objective function of partition also becomes related to the motif information. But, the related research on the directed weighted network needs to be further deepened. The weight of the network has a great influence on the structural attributes of the network, so it is necessary to extend the motif-based clustering to the weighted network. In this paper, a motif-based spectral clustering method

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Devika SV, Et al. "Radio Resource Management Satellite Communication Network MCDM Method." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 10 (2023): 1826–32. http://dx.doi.org/10.17762/ijritcc.v11i10.8759.

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Worldwide deployment of heterogeneous wireless networks is growing as a result of consumer demand for connectivity at all times and in all places. These customers' interest in multimedia apps like video streaming and VoIP, which demand tight Quality of Service (QoS) support, is growing at the same time. With such limitations, provisioning network resources is a difficult undertaking. In fact, it might be challenging for a network operator to identify trustworthy criteria to choose the optimum network that ensures user happiness while maximising network utilisation, given the availability of nu

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Zhang, Zhi-hua, En-ke Hou, and Xiao xia Luo. "Integration Method of Three-dimensional Complex Tunnel Network Model." International Journal of Engineering and Technology 3, no. 5 (2011): 533–39. http://dx.doi.org/10.7763/ijet.2011.v3.281.

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Peng, Wu. "The Cognitive Ad-hoc Network Spectrum - Routing Selection Method." International Journal of Future Generation Communication and Networking 6, no. 6 (2013): 133–42. http://dx.doi.org/10.14257/ijfgcn.2013.6.6.14.

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M., Kalmuratov, Baynazarov A., and Maysanova A. "METHOD OF INSTALLING A WIRELESS NETWORK Wi-Fi CONNECTION." American Journal of Applied Science and Technology 03, no. 05 (2023): 46–50. http://dx.doi.org/10.37547/ajast/volume03issue05-10.

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Undoubtedly, the important wireless technology is now undeniable, as fewer people turn to wired solutions every day. Nowadays, an increasing number of users rely on wireless technology due to mobility, convenience and affordability.

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Pan, Lei, He Xu Sun, Lan Fang Fu, Bin Liu, Ran Gao, and Bei Bei Wang. "Research on TZSI Control Method." Advanced Materials Research 773 (September 2013): 51–57. http://dx.doi.org/10.4028/www.scientific.net/amr.773.51.

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In transformer-Z-source inverters (TZSI), the impedance networks consist of a transformer and one capacitor. While maintaining the main features of traditional Z-source network, the new networks exhibit some unique advantages, such as the increased voltage gain and reduced voltage stress in the voltage-fed TZSI, when the turns ratio of the transformer windings is over 1. This paper contributes to the ac small signal modeling and analysis of TZSI in continuous conduction mode. The ac small signal model considers the dynamics introduced by network uniquely contained in TZSI. And a double loop co

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Ma, Jinlong, Peng Wang, and Huijia Li. "Directed Network Disassembly Method Based on Non-Backtracking Matrix." Applied Sciences 12, no. 23 (2022): 12047. http://dx.doi.org/10.3390/app122312047.

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Network disassembly refers to the removal of the minimum set of nodes to split the network into disconnected sub-part to achieve effective control of the network. However, most of the existing work only focuses on the disassembly of undirected networks, and there are few studies on directed networks, because when the edges in the network are directed, the application of the existing methods will lead to a higher cost of disassembly. Aiming at fixing the problem, an effective edge module disassembly method based on a non-backtracking matrix is proposed. This method combines the edge module spec

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Wang, Lu, Yong Quan Liang, Qi Jia Tian, Jie Yang, Chao Song, and Zhuang Wu. "A Community Detection Method Based on Multi-Objective Optimization Method." Applied Mechanics and Materials 571-572 (June 2014): 177–82. http://dx.doi.org/10.4028/www.scientific.net/amm.571-572.177.

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Community detection in complex network has been an active research area in data mining and machine learning. This paper proposed a community detection method based on multi-objective evolutionary algorithm, named CDMOEA, which tries to find the Pareto front by maximize two objectives, community score and community fitness. Fast and Elitist Multi-objective Genetic Algorithm is used to attained a set of optimal solutions, and then use Modularity function to choose the best one from them. The locus based adjacency representation is used to realize genetic representation, which ensures the effecti

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Snidero, Silvia, Roberto Corradetti, and Dario Gregori. "network scale-up method." Advances in Methodology and Statistics 1, no. 2 (2004): 395–405. http://dx.doi.org/10.51936/rufc6731.

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The network scale-up method is a social network estimator for the size of hidden or hard-to-count subpopulations. These estimators are based on a simple model which have however strong assumptions. The basic idea is that the proportion of the mean number of people known by respondent in a subpopulation E of T of size e is the same of the proportion that the e subpopulation E forms in general population T of size t: mc = t , where c is the number of persons known by each respondent and m is the mean number of persons known by each respondent in the subpopulation E. The persons known by every su

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Bubboloni, Daniela, and Michele Gori. "The flow network method." Social Choice and Welfare 51, no. 4 (2018): 621–56. http://dx.doi.org/10.1007/s00355-018-1131-7.

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Gamble, A. B., A. R. Conn, and W. R. Pulleyblank. "A network penalty method." Mathematical Programming 50, no. 1-3 (1991): 53–73. http://dx.doi.org/10.1007/bf01594924.

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Xiang, Huaikun. "Urban Road Network Emergency: An Integrative Vulnerability Identification Method." Complexity 2021 (June 11, 2021): 1–20. http://dx.doi.org/10.1155/2021/6325578.

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The vulnerability of an urban road network is affected by many factors, such as internal road network layout, network structure strength, and external destructive events, which have great uncertainty and complexity. Thus, there is still no unified and definite vulnerability analysis scheme available to cities. This paper proposes an integrative vulnerability identification method for urban road networks, which mainly relates to the vulnerability connotation and characteristics analysis of urban road networks during emergency, and vulnerability comprehensive evaluation indices design based on u

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NICHEPORUK, A., A. NICHEPORUK, Y. NICHEPORUK, and A. KAZANTSEV. "METHOD OF DETECTING FRAGMENTS OF BOTNETS BASED ON THE ANALYSIS OF NETWORK TRAFFIC." Herald of Khmelnytskyi National University. Technical sciences 283, no. 2 (2020): 141–49. https://doi.org/10.31891/2307-5732-2020-283-2-141-149.

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The paper proposes a method of detecting fragments of botnets based on the analysis of network traffic. The proposed method depends primarily on the temporary relationships of malicious actions between computers on the network and does not depend on the architectures of botnets and the tools used to manage them. The method is based on the representation of malicious activity performed by bots in the local network in the form of a weighted oriented graph, where the vertices are the hosts of the network, and the edges are the connections between the hosts. In order to detect malicious activity o

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Wang, Chunlin, Ning Huang, Yanan Bai, and Shuo Zhang. "A method of network topology optimization design considering application process characteristic." Modern Physics Letters B 32, no. 07 (2018): 1850091. http://dx.doi.org/10.1142/s0217984918500914.

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Communication networks are designed to meet the usage requirements of users for various network applications. The current studies of network topology optimization design mainly considered network traffic, which is the result of network application operation, but not a design element of communication networks. A network application is a procedure of the usage of services by users with some demanded performance requirements, and has obvious process characteristic. In this paper, we first propose a method to optimize the design of communication network topology considering the application process

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