Relevant bibliographies by topics / Network method

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Network method'

Author: Grafiati
Published: 28 May 2022
Last updated: 30 July 2025

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Journal articles on the topic "Network method"

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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. First, to increase the network’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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Dissertations / Theses on the topic "Network method"

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Dunn, Nathan A. "A Novel Neural Network Analysis Method Applied to Biological Neural Networks." Thesis, view abstract or download file of text, 2006. http://proquest.umi.com/pqdweb?did=1251892251&sid=2&Fmt=2&clientId=11238&RQT=309&VName=PQD.

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Thesis (Ph. D.)--University of Oregon, 2006.<br>Typescript. Includes vita and abstract. Includes bibliographical references (leaves 122- 131). Also available for download via the World Wide Web; free to University of Oregon users.
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Mesquine, Abdellah. "Fibre Network Generation andAnalysis : Method for simulation of inhomogeneous static fibre networks." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-175084.

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In paper optics, advanced modeling of the interaction of light with complex structuresare required for optimization of the optical properties of paper. Monte Carlosimulation routines have been developed in an Open Source project, PaperOpt, inorder to simulate light scattering in paper. The goal of the project is to make the toolmore modular and extensible so that researchers within the paper optics field canmake their own contributions to the model. This thesis is a part of Open PaperOptproject and its goal is to generate paper structures that resemble real paper sheets.This Master’s thesis de
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Liere, Diederik Willem van. "Network horizon and the dynamics of network positions a multi-method multi-level longitudinal study of interfirm networks /." [Rotterdam] : Rotterdam : Erasmus Research Institute of Management (ERIM), Erasmus University Rotterdam ; Erasmus University [Host], 2007. http://hdl.handle.net/1765/10181.

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Chen, Youping. "Neural network approximation for linear fitting method." Ohio : Ohio University, 1992. http://www.ohiolink.edu/etd/view.cgi?ohiou1172243968.

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Luan, Wenpeng. "Voltage ranking using artificial neural network method." Thesis, University of Strathclyde, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.366960.

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Dandachi, Najib H. "Network flow method for power system analysis." Thesis, Imperial College London, 1989. http://hdl.handle.net/10044/1/47398.

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Leonardi, Suryanto Felix 1958, and Suryanto Felix 1958 Leonardi. "Switched-capacitor network synthesis using leapfrog method." Thesis, The University of Arizona, 1989. http://hdl.handle.net/10150/558107.

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Wei, Yuchen. "Reliability Analysis Method and Network Optimization of 5G Backhaul Network for Operators." Thesis, The University of Sydney, 2021. https://hdl.handle.net/2123/25483.

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Communication network reliability analysis is of great significance in the practice of network construction management and operation of telecom operators. It can provide an important scientific basis for the formulation of network construction strategy and the optimization and adjustment of network performance. Combining the theoretical results of reliability analysis with engineering application practice effectively in communication network operation has always been a research difficulty in communication network operation, which has high theoretical research value and market application prosp
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Sung, Woong Je. "A neural network construction method for surrogate modeling of physics-based analysis." Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/43721.

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A connectivity adjusting learning algorithm, Optimal Brain Growth (OBG) was proposed. Contrast to the conventional training methods for the Artificial Neural Network (ANN) which focus on the weight-only optimization, the OBG method trains both weights and connectivity of a network in a single training process. The standard Back-Propagation (BP) algorithm was extended to exploit the error gradient information of the latent connection whose current weight has zero value. Based on this, the OBG algorithm makes a rational decision between a further adjustment of an existing connection weight and a
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Jiang, Qi. "Nodes cooperation trust method over ad hoc network." Thesis, Wichita State University, 2011. http://hdl.handle.net/10057/5042.

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An ad hoc network consists of wireless nodes that communicate through cooperation with each other, and operate independently of additional network devices such as routers and switches. These networks are self-sufficient and distributed in nature which are most widely used in the areas where there is little or no infrastructure available, like battlefields, weather forecast applications, etc. Recently ad hoc networks have been deployed in many places and have become a part of everyone’s life. Devices such as laptops, smartphones, and netbooks are using it as one option for wireless networks. Th
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Books on the topic "Network method"

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Horno, Montijano Jośe, and Research Signpost (Trivandrum India), eds. Network simulation method. Research Signpost, 2002.

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M. L. (Mart L.) Molle. A new binary logarithmic arbitration method for Ethernet. Computer Systems Research Institute, University of Toronto, 1994.

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IEEE Computer Society. Technical Committee on Computer Communications., ed. Token-passing bus access method and physical layer specifications: IEEE standards for local area networks. Institute of Electrical and Electronics Engineers, 1985.

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K, Kokula Krishna Hari, ed. Method to Provide Mobile Signal when the Network Provider Has Failed. Association of Scientists, Developers and Faculties, 2016.

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Gannon, Timothy Paul. The dual decomposition method and its application to an interdicted network. Naval Postgraduate School, 1989.

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Vartiainen, Perttu. Method of description for the urban network in the Baltic Sea region. Ministry of the Environment, 2000.

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Geological Survey (U.S.). National Mapping Division., ed. Neural network method for sharpening Landsat thermal data from higher resolution multispectral data. U.S. Dept. of the Interior, U.S. Geological Survey, National Mapping Division, 1997.

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Geological Survey (U.S.). National Mapping Division, ed. Neural network method for sharpening Landsat thermal data from higher resolution multispectral data. U.S. Dept. of the Interior, U.S. Geological Survey, National Mapping Division, 1997.

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IEEE Computer Society. Technical Committee on Computer Communications., Institute of Electrical and Electronics Engineers., International Organization for Standardization, and International Electrotechnical Commission, eds. Information technology -- telecommunications and information exchange between systems -- local and metropolitan area networks -- specific requirements--: Part 5: Token ring access method and physical layer specifications. Institute of Electrical and Electronics Engineers, 1995.

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IEEE Computer Society. LAN MAN Standards Committee., International Organization for Standardization, International Electrotechnical Commission, Institute of Electrical and Electronics Engineers., and IEEE Standards Board, eds. Information technology -- telecommunications and information exchange between systems -- local and metropolitan area networks -- specific requirements --: Part 5: Token ring access method and physical layer specifications. 3rd ed. Institute of Electrical and Electronics Engineers, 1998.

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Book chapters on the topic "Network method"

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Webb, Benjamin L. J., David Holmes, Chun Li, Jin Z. Zhang, and Matthew T. Lloyd. "Hybrid Network Method." In Encyclopedia of Nanotechnology. Springer Netherlands, 2012. http://dx.doi.org/10.1007/978-90-481-9751-4_100302.

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Krebs, Matthias. "Network Analysis Method." In Springer Texts in Business and Economics. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-47206-0_12.

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Chowdhury, Dhiman Deb. "Method of Time Distribution." In NextGen Network Synchronization. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-71179-5_6.

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Henning, Michael A., and Jan H. van Vuuren. "The probabilistic method." In Graph and Network Theory. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-03857-0_20.

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Kosztyán, Zs T., and J. Kiss. "Stochastic Network Planning Method." In Advanced Techniques in Computing Sciences and Software Engineering. Springer Netherlands, 2009. http://dx.doi.org/10.1007/978-90-481-3660-5_44.

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Wang, Xuewen, Jiacheng Xie, and Suhua Li. "Virtual Assembly Network Method." In Virtual Reality Technology in Mining Machinery. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-4408-5_7.

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Lindgren, Peter. "Project Method." In Network Based High Speed Product Development. River Publishers, 2022. http://dx.doi.org/10.1201/9781003338901-4.

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Kłos, Andrzej. "Network Solution Method Using Algebraic Network Model." In Mathematical Models of Electrical Network Systems. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-52178-7_11.

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Hernandez Fernandez, Javier, Aymen Omri, and Roberto Di Pietro. "Authentication Method for PLC Network." In Physical Layer Security in Power Line Communications. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-57349-1_8.

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McLean, Scott, Mitchell Naughton, Gemma J. M. Read, et al. "The Accident Network (ACCINET) Method." In Systems Thinking Methods in Sport. Routledge, 2024. http://dx.doi.org/10.4324/9781003259473-15.

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Conference papers on the topic "Network method"

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Qi, Jianyu, Zhichun Jia, Xing Xing, and Shuyan Dong. "Optimizing Method for Network Traffic Classification Based on LSTM Network." In 2025 IEEE 14th Data Driven Control and Learning Systems (DDCLS). IEEE, 2025. https://doi.org/10.1109/ddcls66240.2025.11065814.

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Abbas, Haydeer Mohamad, Shashidhara K. S, D. Balamurugan, Baraneetharan E, and K. S. Vigneshwaran. "Improved Deep Reinforcement Learning Based Network Slicing Method in 5G Networks." In 2025 3rd International Conference on Integrated Circuits and Communication Systems (ICICACS). IEEE, 2025. https://doi.org/10.1109/icicacs65178.2025.10968730.

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Oguchi, Kimio. "Network design method for wavelength routing networks." In 2009 14th OptoElectronics and Communications Conference (OECC). IEEE, 2009. http://dx.doi.org/10.1109/oecc.2009.5214723.

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Burkov, V. N., and I. V. Burkova. "Network programming method." In UKACC International Conference on CONTROL 2010. Institution of Engineering and Technology, 2010. http://dx.doi.org/10.1049/ic.2010.0275.

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Hossain, Shakhawath, Per Bergström, Sohan Sarangi, and Tetsu Uesaka. "Computational Design of Fibre Network by Discrete Element Method." In Advances in Pulp and Paper Research, Oxford 2017, edited by W. Batchelor and D. Söderberg. Fundamental Research Committee (FRC), Manchester, 2017. http://dx.doi.org/10.15376/frc.2017.2.651.

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Soft fibre networks, typically seen in bathroom tissues, kitchen towels, and personal-care products, have properties that are intricately affected by the details of fibre geometry, 3D-network structures, and processing conditions. Designing such materials and products for better performance, while controlling cost, is especially a challenge in today’s fast paced product development. This paper concerns the development of a new, robust computational design platform for the design of soft fibre networks. We have used particle-based methods, particularly, Discrete Element Method (DEM), to model f
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Zhang, Yihui, Huifeng Zhao, Wenjian Hu, and Jingquan Li. "Network slice optimization method for wireless access networks." In 2018 IEEE International Conference on Electronics and Communication Engineering (ICECE). IEEE, 2018. http://dx.doi.org/10.1109/icecome.2018.8644858.

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Wen, Yufei, Lei Guo, Zhumin Chen, and Jun Ma. "Network Embedding Based Recommendation Method in Social Networks." In Companion of the The Web Conference 2018. ACM Press, 2018. http://dx.doi.org/10.1145/3184558.3186904.

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Nishimatsu, Ken, Akiya Inoue, and Takeshi Kurosawa. "Service-demand-forecasting method using multiple data sources." In Networks 2006. 12th International Telecommunications Network Strategy and Planning Symposium. IEEE, 2006. http://dx.doi.org/10.1109/netwks.2006.300361.

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Nagasawa, Yurina, Tomotaka Kimura, Takanori Kudo, and Kouji Hirata. "Estimation method of network availability with convolutional neural networks." In 2019 IEEE International Conference on Consumer Electronics - Taiwan (ICCE-TW). IEEE, 2019. http://dx.doi.org/10.1109/icce-tw46550.2019.8991804.

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Xu, Xin, Zhixiang Gao, Jun Cai, and Dongming Bian. "A Dynamic Network Simulation Method of Mega-Constellation Networks." In 2022 IEEE 8th International Conference on Computer and Communications (ICCC). IEEE, 2022. http://dx.doi.org/10.1109/iccc56324.2022.10066008.

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Reports on the topic "Network method"

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Xu, Ying, and Jennifer Corbett. Using Network Method to Measure Financial Interconnection. National Bureau of Economic Research, 2019. http://dx.doi.org/10.3386/w26499.

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Horneman, Angela, and Nathan Dell. Smart Collection and Storage Method for Network Traffic Data. Defense Technical Information Center, 2014. http://dx.doi.org/10.21236/ada609898.

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Kirichek, Galina, Vladyslav Harkusha, Artur Timenko, and Nataliia Kulykovska. System for detecting network anomalies using a hybrid of an uncontrolled and controlled neural network. [б. в.], 2020. http://dx.doi.org/10.31812/123456789/3743.

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In this article realization method of attacks and anomalies detection with the use of training of ordinary and attacking packages, respectively. The method that was used to teach an attack on is a combination of an uncontrollable and controlled neural network. In an uncontrolled network, attacks are classified in smaller categories, taking into account their features and using the self- organized map. To manage clusters, a neural network based on back-propagation method used. We use PyBrain as the main framework for designing, developing and learning perceptron data. This framework has a suffi
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Bobashev, Georgiy, R. Joey Morris, Elizabeth Costenbader, and Kyle Vincent. Assessing network structure with practical sampling methods. RTI Press, 2018. http://dx.doi.org/10.3768/rtipress.2018.op.0049.1805.

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Using data from an enumerated network of worldwide flight connections between airports, we examine how sampling designs and sample size influence network metrics. Specifically, we apply three types of sampling designs: simple random sampling, nonrandom strategic sampling (i.e., selection of the largest airports), and a variation of snowball sampling. For the latter sampling method, we design what we refer to as a controlled snowball sampling design, which selects nodes in a manner analogous to a respondent-driven sampling design. For each design, we evaluate five commonly used measures of netw
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KHVOENKOVA, Nina, and Matthieu DELORME. An Optimal Method to Model Transient Flows in 3D Discrete Fracture Network. Cogeo@oeaw-giscience, 2011. http://dx.doi.org/10.5242/iamg.2011.0088.

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Liu, Yong. Neural Network Model Selection Using Asymptotic Jackknife Estimator and Cross-Validation Method. Defense Technical Information Center, 1993. http://dx.doi.org/10.21236/ada264960.

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Pietrobelli, Carlo, and Elisa Giuliani. Social Network Analysis Methodologies for the Evaluation of Cluster Development Programs. Inter-American Development Bank, 2011. http://dx.doi.org/10.18235/0008963.

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Cluster development programs (CDPs) have been adopted widely in many countries worldwide. Many such programs aim to promote economic development by forming and strengthening inter-organizational networks. Despite their widespread diffusion, we know very little about CDP outputs or the impact CDPs have on host regions and their populations. Evaluation studies are beginning to appear, but the overall concern is that a distinct evaluation concept and method with a focus on CDPs is not yet available. The objective of this paper is to address this limitation, by proposing a novel methodological app
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Melsen, T., and S. Blake. MAC-Forced Forwarding: A Method for Subscriber Separation on an Ethernet Access Network. RFC Editor, 2006. http://dx.doi.org/10.17487/rfc4562.

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Meyer, P. D. A quantitative method for groundwater surveillance monitoring network design at the Hanford Site. Office of Scientific and Technical Information (OSTI), 1993. http://dx.doi.org/10.2172/10115524.

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Yaroshchuk, Svitlana O., Nonna N. Shapovalova, Andrii M. Striuk, Olena H. Rybalchenko, Iryna O. Dotsenko, and Svitlana V. Bilashenko. Credit scoring model for microfinance organizations. [б. в.], 2020. http://dx.doi.org/10.31812/123456789/3683.

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The purpose of the work is the development and application of models for scoring assessment of microfinance institution borrowers. This model allows to increase the efficiency of work in the field of credit. The object of research is lending. The subject of the study is a direct scoring model for improving the quality of lending using machine learning methods. The objective of the study: to determine the criteria for choosing a solvent borrower, to develop a model for an early assessment, to create software based on neural networks to determine the probability of a loan default risk. Used rese
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