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Articles de revues sur le sujet « Network convergence »

Auteur : Grafiati

Publié le 4 juin 2021

Mis à jour le 25 juillet 2025

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1

Bader, Joel S. "Grand network convergence." Genome Biology 12, no. 6 (2011): 306. http://dx.doi.org/10.1186/gb-2011-12-6-306.

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Kobayakawa, Shunsuke, and Hirokazu Yokoi. "Predictor Using an Error-Convergence Neuron Network and its Application to Electrocardiograms." Journal of Advanced Computational Intelligence and Intelligent Informatics 15, no. 1 (2011): 21–33. http://dx.doi.org/10.20965/jaciii.2011.p0021.

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The output error of a neuron network cannot converge at zero, even if the training for a neuron network is iterated many times. “Error-convergence neuron network” in which the output error of a singleoutput system uses neuron networks with multiplestep convergence, has been designed to resolve this problem. The output error is converged at zero by setting infinite steps of the neuron network. Three types of neuron network systems also have been designed. They are “Error-convergence parallel neuron network,” “Error-convergence recurrent neuron network,” and “Error-convergence parallel recurrent

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Ahmed Ali, Adel, and Ahmed M. Al-Naamany. "Converged Networking: A Review of Concepts and Technologies." Sultan Qaboos University Journal for Science [SQUJS] 5 (December 1, 2000): 209. http://dx.doi.org/10.24200/squjs.vol5iss0pp209-225.

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Converged networking is an emerging technology thrust that integrates voice, video, and data traffic on a single network. Converged networking encompasses several aspects, all of which are related to the aggregation of networking activity. Such aspects include, Payload convergence, Protocol convergence, Physical convergence, Device convergence, Application convergence, Technology convergence, etc. In recent years the Internet has developed into a global data network that is highly accepted as a multimedia information platform, which has the potential to develop into an alternative carrier netw

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Cao, Xun. "Global Networks and Domestic Policy Convergence: A Network Explanation of Policy Changes." World Politics 64, no. 3 (2012): 375–425. http://dx.doi.org/10.1017/s0043887112000081.

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National economies are embedded in complex networks such as trade, capital flows, and intergovernmental organizations (IGOs). These globalization forces impose differential impacts on national economies depending on a country's network positions. This article addresses the policy convergence-divergence debate by focusing on how networks at the international level affect domestic fiscal, monetary, and regulatory policies. The author presents two hypotheses: first, similarity in network positions induces convergence in domestic economic policies as a result of peer competitive pressure. Second,

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Jamalipour, Abbas, Nei Kato, Hsiao-Hwa Chen, and Kyung Pyo Jun. "Broadband convergence Network (BcN)." Journal of Communications and Networks 8, no. 4 (2006): 363–68. http://dx.doi.org/10.1109/jcn.2006.6182784.

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Kamal Bashah, Nor Shahniza, Nor Haizon Husin, Syaripah Ruzaini Syed Aris, Norjansalika Janom, and Noor Habibah Arshad. "The optimization of leased line distribution at the EDGE of local access network via WAN convergence network." Indonesian Journal of Electrical Engineering and Computer Science 16, no. 1 (2019): 333. http://dx.doi.org/10.11591/ijeecs.v16.i1.pp333-341.

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Managing the multiple services of the leased line at the same location is quite critical especially when the resource become highly utilized. Bundling the several network resource components into a one box by simplifying the multiple networks to a single network can help to reduce the utilization of network resources. This paper presents a study on optimiziation of leased line distribution at the EDGE of Local Access Network via WAN convergence network. In this study, a WAN Convergence Network is designed which intends to use only a single leased line network in a location rather than multiple

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Tan, Haoming, Junyun Wu, Hongjie Guan, et al. "A New Varying-Factor Finite-Time Recurrent Neural Network to Solve the Time-Varying Sylvester Equation Online." Mathematics 12, no. 24 (2024): 3891. https://doi.org/10.3390/math12243891.

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This paper presents a varying-parameter finite-time recurrent neural network, called a varying-factor finite-time recurrent neural network (VFFTRNN), which is able to solve the solution of the time-varying Sylvester equation online. The proposed neural network makes the matrix coefficients vary with time and can achieve convergence in a finite time. Apart from this, the performance of the network is better than traditional networks in terms of robustness. It is theoretically proved that the proposed neural network has super-exponential convergence performance. Simulation results demonstrate th

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Whigham, P. A., G. Dick, and M. Parry. "Network rewiring dynamics with convergence towards a star network." Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 472, no. 2194 (2016): 20160236. http://dx.doi.org/10.1098/rspa.2016.0236.

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Network rewiring as a method for producing a range of structures was first introduced in 1998 by Watts & Strogatz ( Nature 393 , 440–442. ( doi:10.1038/30918 )). This approach allowed a transition from regular through small-world to a random network. The subsequent interest in scale-free networks motivated a number of methods for developing rewiring approaches that converged to scale-free networks. This paper presents a rewiring algorithm (RtoS) for undirected, non-degenerate, fixed size networks that transitions from regular, through small-world and scale-free to star-like networks. Appli

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Sasikala, P. "Cloud Computing Towards Technological Convergence." International Journal of Cloud Applications and Computing 1, no. 4 (2011): 44–59. http://dx.doi.org/10.4018/ijcac.2011100104.

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With the popularization and improvement of social and industrial IT development, information appears to explosively increase, and people put much higher expectations on the services of computing, communication and network. Today’s public communication network is developing in the direction that networks are widely interconnected using communication network infrastructure as backbone and Internet protocols; at the same time, cloud computing, a computing paradigm in the ascendant, provides new service modes. Communication technology has the trend of developing towards computing technology and ap

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Beshley, H., Y. Shkoropad, M. Beshley, and M. Klymash. "CONVERGENCE OF HETEROGENEOUS WIRELESS NETWORKS FOR FUTURE COMMUNICATIONS: ARCHITECTURE, QOS AND RESOURCE MANAGEMENT." Information and communication technologies, electronic engineering 2, no. 2 (2022): 20–32. http://dx.doi.org/10.23939/ictee2022.02.020.

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Scientific and theoretical approaches to the implementation of a heterogeneous mobile communication network based on SDN/NFV and SDR technologies are described. The architecture of the future heterogeneous network is proposed, taking into account the evolution of emerging standards and key technologies. An algorithm for dynamic bandwidth allocation and reservation between several logical channels at a certain moment of time to provide QoS for information flows in future networks is created. A simulation model of network traffic service with parameters corresponding to real networks has been ma

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Chang, Gee-Kung, and Lin Cheng. "The benefits of convergence." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 374, no. 2062 (2016): 20140442. http://dx.doi.org/10.1098/rsta.2014.0442.

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A multi-tier radio access network (RAN) combining the strength of fibre-optic and radio access technologies employing adaptive microwave photonics interfaces and radio-over-fibre (RoF) techniques is envisioned for future heterogeneous wireless communications. All-band radio spectrum from 0.1 to 100 GHz will be used to deliver wireless services with high capacity, high link speed and low latency. The multi-tier RAN will improve the cell-edge performance in an integrated heterogeneous environment enabled by fibre–wireless integration and networking for mobile fronthaul/backhaul, resource sharing

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Park, Sang-Joon, Jong-Chan Lee, and Sung-Yun Shin. "A Scheme of Access Network Management in Convergence Networks." Journal of the Korea Society of Computer and Information 17, no. 11 (2012): 93–99. http://dx.doi.org/10.9708/jksci/2012.17.11.093.

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Santos, Justino, Diogo Gomes, Susana Sargento, et al. "Multicast/broadcast network convergence in next generation mobile networks." Computer Networks 52, no. 1 (2008): 228–47. http://dx.doi.org/10.1016/j.comnet.2007.09.002.

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Cortés-Polo, David, José-Luis González-Sánchez, Francisco-Javier Rodríguez-Pérez, and Javier Carmona-Murillo. "Mobility management in packet transport networks for network convergence." Transactions on Emerging Telecommunications Technologies 26, no. 5 (2013): 749–59. http://dx.doi.org/10.1002/ett.2705.

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Tsioliaridou, Ageliki, and Vassilis Tsaoussidis. "Fast convergence to network fairness." Journal of Systems and Software 83, no. 5 (2010): 745–62. http://dx.doi.org/10.1016/j.jss.2009.11.715.

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Dixit, Sudhir. "On Fixed-Mobile Network Convergence." Wireless Personal Communications 38, no. 1 (2006): 55–65. http://dx.doi.org/10.1007/s11277-006-9042-9.

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Rost, P., R. Boutaba, K. Doppler, and A. Gumaste. "Recent Advances in Network Convergence." Computer Networks 55, no. 7 (2011): 1455–58. http://dx.doi.org/10.1016/j.comnet.2011.04.002.

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Wódczak, Michal. "Convergence Aspects of Autonomic Cooperative Networks." International Journal of Information Technology and Web Engineering 6, no. 4 (2011): 51–62. http://dx.doi.org/10.4018/jitwe.2011100104.

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The current efforts across industry and academia are to develop new paradigms that enable ubiquitous on-demand service provision. This aim may be achievable because of the envisaged deployment of cutting-edge technologies such as cooperative transmission. However, a real advancement is only attainable when autonomic system design principles are taken into account. Looking at the concept of the Relay Enhanced Cell, one may come across commonalities with Mobile Ad-hoc Networks. Especially in Local Area scenarios, Base Stations seem to resemble advanced Access Points, while fixed and movable Rela

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Cui, Hongyan, Shaohua Tang, Fangfang Sun, Yue Xu, and Xiaoli Yang. "Topological Embedding Feature Based Resource Allocation in Network Virtualization." Mathematical Problems in Engineering 2014 (2014): 1–10. http://dx.doi.org/10.1155/2014/271493.

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Virtualization provides a powerful way to run multiple virtual networks on a shared substrate network, which needs accurate and efficient mathematical models. Virtual network embedding is a challenge in network virtualization. In this paper, considering the degree of convergence when mapping a virtual network onto substrate network, we propose a new embedding algorithm based on topology mapping convergence-degree. Convergence-degree means the adjacent degree of virtual network’s nodes when they are mapped onto a substrate network. The contributions of our method are as below. Firstly, we map v

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YEUNG, DANIEL S., SHENSHAN QIU, ERIC C. C. TSANG, and XIZHAO WANG. "A GENERAL UPDATING RULE FOR DISCRETE HOPFIELD-TYPE NEURAL NETWORK WITH TIME-DELAY AND THE CORRESPONDING SEARCH ALGORITHM." International Journal of Computational Intelligence and Applications 01, no. 04 (2001): 399–412. http://dx.doi.org/10.1142/s1469026801000329.

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In this paper, the Hopfield neural network with delay (HNND) is studied from the standpoint of regarding it as an optimizing computational model. Two general updating rules for networks with delay (GURD) are given based on Hopfield-type neural networks with delay for optimization problems and characterized by dynamic thresholds. It is proved that in any sequence of updating rule modes, the GURD monotonously converges to a stable state of the network. The diagonal elements of the connection matrix are shown to have an important influence on the convergence process, and they represent the relati

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Blaszczyk, Andreas, Reto Flückiger, Thomas Müller, and Carl-Olof Olsson. "Convergence behaviour of coupled pressure and thermal networks." COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering 33, no. 4 (2014): 1233–50. http://dx.doi.org/10.1108/compel-12-2012-0378.

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Purpose – The purpose of this paper is to present a method for thermal computations of power devices based on a coupling between thermal and pressure networks. The concept of the coupling as well as the solution procedure is explained. The included examples demonstrate that the new method can be efficiently used for design of transformers and other power devices. Design/methodology/approach – The bidirectional propagation of temperature signal is introduced to the pressure network, which enables control of the power flow and a close coupling to the thermal network. The solution method is based

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Bao, Chunhui, Yifei Pu, and Yi Zhang. "Fractional-Order Deep Backpropagation Neural Network." Computational Intelligence and Neuroscience 2018 (July 3, 2018): 1–10. http://dx.doi.org/10.1155/2018/7361628.

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In recent years, the research of artificial neural networks based on fractional calculus has attracted much attention. In this paper, we proposed a fractional-order deep backpropagation (BP) neural network model with L2 regularization. The proposed network was optimized by the fractional gradient descent method with Caputo derivative. We also illustrated the necessary conditions for the convergence of the proposed network. The influence of L2 regularization on the convergence was analyzed with the fractional-order variational method. The experiments have been performed on the MNIST dataset to

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Chu, Lina. "Design and Application of BP Neural Network Optimization Method Based on SIWSPSO Algorithm." Security and Communication Networks 2022 (April 21, 2022): 1–9. http://dx.doi.org/10.1155/2022/2960992.

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BP neural network method can deal with nonlinear and uncertain problems well and is widely used in the construction of classification, clustering, prediction, and other models. However, BP neural network method has some limitations in fitting nonlinear functions, such as slow convergence speed and easy local optimal convergence rather than global optimal convergence. In order to solve the insufficiency, the optimization approach applying BP neural networks is discussed. This paper proposes a simplified PSO algorithm based on stochastic inertia weight (SIWSPSO) algorithm to optimize BP neural n

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Ding, Zhaolong, Huijie Liu, Feng Tian, Zijian Yang, and Nan Wang. "Fast-Convergence Reinforcement Learning for Routing in LEO Satellite Networks." Sensors 23, no. 11 (2023): 5180. http://dx.doi.org/10.3390/s23115180.

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Fast convergence routing is a critical issue for Low Earth Orbit (LEO) constellation networks because these networks have dynamic topology changes, and transmission requirements can vary over time. However, most of the previous research has focused on the Open Shortest Path First (OSPF) routing algorithm, which is not well-suited to handle the frequent changes in the link state of the LEO satellite network. In this regard, we propose a Fast-Convergence Reinforcement Learning Satellite Routing Algorithm (FRL–SR) for LEO satellite networks, where the satellite can quickly obtain the network link

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Kim, Yu-Doo, and Il-Young Moon. "P2P Network Simulation System for Performance Evaluation in Convergence Networks." Journal of information and communication convergence engineering 9, no. 4 (2011): 396–400. http://dx.doi.org/10.6109/jicce.2011.9.4.396.

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Kim, Junho, SeungGwan Lee, and Sungwon Lee. "Mesh Network Convergence Management System Using Software-Defined Network." Mobile Information Systems 2018 (October 17, 2018): 1–13. http://dx.doi.org/10.1155/2018/7157948.

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The Internet penetration rate is rising all over the world. In South Korea, there is no area which does not have Ethernet ports and Wi-Fi. So many people are familiar with network, Internet. However, there are still many countries and regions that do not know the weather today because the Internet is not available yet. To solve this problem, many people are studying the mesh network and actually building it and making efforts to spread the Internet. But, in reality, software that can build and manage such a mesh network is insufficient. In order to solve this problem, this paper proposes Gathe

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Zhang, Q. T., Jiayi Chen, and Hongbo Zhu. "Network convergence: theory, architectures, and applications." IEEE Wireless Communications 21, no. 6 (2014): 48–53. http://dx.doi.org/10.1109/mwc.2014.7000971.

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Azeem, Shaikh, and Satyendra Sharma. "Convergence In Future Wireless Network Technology." Oriental journal of computer science and technology 10, no. 1 (2017): 41–46. http://dx.doi.org/10.13005/ojcst/10.01.06.

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The communications sector is undergoing significant changes, with the emergence of a number of platforms available to provide a different range of services. Some of these platforms are complementary to each other, while others are competitive, or can provide a valid substitute for some of the services provided. Up till now, the most important communications platform in most of the developing countries has been the public switched telecommunication network (PSTN) which provides access to all households and buildings. This universality in providing access has also meant that the network has gene

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Naumer, Marcus J., Leonie Ratz, Yavor Yalachkov, et al. "Visuohaptic convergence in a corticocerebellar network." European Journal of Neuroscience 31, no. 10 (2010): 1730–36. http://dx.doi.org/10.1111/j.1460-9568.2010.07208.x.

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Aggarwal, Vinay, Olaf Maennel, Jeffrey Mogul, and Allyn Romanow. "Workshop on network-I/O convergence." ACM SIGCOMM Computer Communication Review 33, no. 5 (2003): 75–80. http://dx.doi.org/10.1145/963985.963994.

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Luo, Kai, and Shutter Zor. "China’s non-ferrous metal recycling technology convergence and driving factors: A quadratic assignment procedure analysis based on patent collaboration-based network structural hole." PLOS ONE 17, no. 8 (2022): e0271694. http://dx.doi.org/10.1371/journal.pone.0271694.

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Technological convergence is an important organizational innovation capability, essential for improving the core competitiveness of green and sustainable industries. However, studies have mainly focused on measuring technological convergence and have ignored the factors that affect the capabilities of such convergence capabilities. Thus, this study attempts to bridge this gap by providing an in-depth analysis of the impact of structural holes in inter-organizational technical cooperation networks. This technological convergence is studied from the perspective of a patent. It also considers the

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Šíma, Jiří, Pekka Orponen, and Teemu Antti-Poika. "On the Computational Complexity of Binary and Analog Symmetric Hopfield Nets." Neural Computation 12, no. 12 (2000): 2965–89. http://dx.doi.org/10.1162/089976600300014791.

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We investigate the computational properties of finite binary- and analog-state discrete-time symmetric Hopfield nets. For binary networks, we obtain a simulation of convergent asymmetric networks by symmetric networks with only a linear increase in network size and computation time. Then we analyze the convergence time of Hopfield nets in terms of the length of their bit representations. Here we construct an analog symmetric network whose convergence time exceeds the convergence time of any binary Hopfield net with the same representation length. Further, we prove that the MIN ENERGY problem f

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LENCZNER, MICHEL, and GHOUTI SENOUCI-BEREKSI. "HOMOGENIZATION OF ELECTRICAL NETWORKS INCLUDING VOLTAGE-TO-VOLTAGE AMPLIFIERS." Mathematical Models and Methods in Applied Sciences 09, no. 06 (1999): 899–932. http://dx.doi.org/10.1142/s0218202599000415.

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We derive the homogenized model of periodic electrical networks which includes resistive devices, voltage-to-voltage amplifiers, sources of tension and sources of current. On the one hand, in considering the homogenized problem, general conditions are stated insuring the existence and uniqueness of the solution. They are formulated in function of the network topology. On the other hand, the two-scale transformation introduced by Arbogast, Douglas and Hornung is adapted to the context of electrical networks. New two-scale. convergence results, inspired by the principle of Allaire's two-scale co

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Devikar, Rohit Nilkanth, D. V. Patil, and V. Chandraprakash. "Study of BGP Convergence Time." International Journal of Electrical and Computer Engineering (IJECE) 6, no. 1 (2016): 413. http://dx.doi.org/10.11591/ijece.v6i1.8106.

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Border Gateway Protocol (BGP), a path vector routing protocol, is a widespread exterior gateway protocol (EGP) in the internet. Extensive deployment of the new technologies in internet, protocols need to have continuous improvements in its behavior and operations. New routing technologies conserve a top level of service availability. Hence, due to topological changes, BGP needs to achieve a fast network convergence. Now a days size of the network growing very rapidly. To maintain the high scalability in the network BGP needs to avoid instability. The instability and failures may cause the netw

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Devikar, Rohit Nilkanth, D. V. Patil, and V. Chandraprakash. "Study of BGP Convergence Time." International Journal of Electrical and Computer Engineering (IJECE) 6, no. 1 (2016): 413. http://dx.doi.org/10.11591/ijece.v6i1.pp413-420.

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Border Gateway Protocol (BGP), a path vector routing protocol, is a widespread exterior gateway protocol (EGP) in the internet. Extensive deployment of the new technologies in internet, protocols need to have continuous improvements in its behavior and operations. New routing technologies conserve a top level of service availability. Hence, due to topological changes, BGP needs to achieve a fast network convergence. Now a days size of the network growing very rapidly. To maintain the high scalability in the network BGP needs to avoid instability. The instability and failures may cause the netw

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Sahinel, Doruk, Simon Rommel, and Idelfonso Tafur Monroy. "Resource Management in Converged Optical and Millimeter Wave Radio Networks: A Review." Applied Sciences 12, no. 1 (2021): 221. http://dx.doi.org/10.3390/app12010221.

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Three convergent processes are likely to shape the future of the internet beyond-5G: The convergence of optical and millimeter wave radio networks to boost mobile internet capacity, the convergence of machine learning solutions and communication technologies, and the convergence of virtualized and programmable network management mechanisms towards fully integrated autonomic network resource management. The integration of network virtualization technologies creates the incentive to customize and dynamically manage the resources of a network, making network functions, and storage capabilities at

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Liu, Qingshan, Jinde Cao, and Guanrong Chen. "A Novel Recurrent Neural Network with Finite-Time Convergence for Linear Programming." Neural Computation 22, no. 11 (2010): 2962–78. http://dx.doi.org/10.1162/neco_a_00029.

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In this letter, a novel recurrent neural network based on the gradient method is proposed for solving linear programming problems. Finite-time convergence of the proposed neural network is proved by using the Lyapunov method. Compared with the existing neural networks for linear programming, the proposed neural network is globally convergent to exact optimal solutions in finite time, which is remarkable and rare in the literature of neural networks for optimization. Some numerical examples are given to show the effectiveness and excellent performance of the new recurrent neural network.

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Feng, Zhijun, Wen Zhou, and Qian Ming. "Embodied Energy Flow Patterns of the Internal and External Industries of Manufacturing in China." Sustainability 11, no. 2 (2019): 438. http://dx.doi.org/10.3390/su11020438.

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The Sino–US trade war has prompted China to re-examine the development of manufacturing, while the energy crisis restricts such development. Scientifically planning industrial energy allocation is important for supporting industrial transformation and the upgrading of manufacturing. The embodied energy flow in China’s manufacturing was investigated by reconstructing the energy flow network; taking a systems perspective, a fine-grained analysis of the emerging patterns and evolution of these flows in the internal and external manufacturing industries was performed, thus providing useful insight

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Li, Jun Yi. "Bp Neural Network Optimized by PSO and its Application in Function Approximation." Advanced Materials Research 945-949 (June 2014): 2413–16. http://dx.doi.org/10.4028/www.scientific.net/amr.945-949.2413.

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BP network is one of the most popular artificial neural networks because of its special advantage such as simple structure, distributed storage, parallel processing, high fault-tolerance performance, etc. However, with its extensive use in recent years, it is discovered that BP algorithm has the defects on slow convergent speed and easy convergence to a local minimum point. The paper proposes a method of BP Neural Network improved by Particle Swarm Optimization (PSO). The hybrid algorithm can not only avoid local minimum, but also raise the speed of network training and reduce the convergence

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Sapoetra, Yudistira Arya, Azwar Riza Habibi, and Lukman Hakim. "Random Number Generator Untuk Bobot Metode Conjugate Gradient Neural Network." Jurnal Derivat: Jurnal Matematika dan Pendidikan Matematika 4, no. 1 (2019): 19–25. http://dx.doi.org/10.31316/j.derivat.v4i1.161.

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This research develops the theory of NN (neural network) by using CG (conjugate gradient) to speed up the process of convergence on a network of NN. CG algorithm is an iterative algorithm to solve simultaneous linear equations on a large scale and it is used to optimize the process of the network on backpropagation. In the process, a Neural netwok doing random weighting on the weight of v and w and this weight will have an effect on the speed of convergence of an algorithm for NN by the method of CG. Furthermore, generating the random numbers to take a sample as a generator in this research of

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Chen, Minghua, Tengwen Zhang, Qinru Chu, et al. "Convergence Analysis of Inclusive Green Growth in China Based on the Spatial Correlation Network." Sustainability 15, no. 16 (2023): 12344. http://dx.doi.org/10.3390/su151612344.

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The purpose of the research is based on the spatial network correlation to explore the convergence path of inclusive green growth. Inclusive green growth is a sustainable development model that emphasizes the integration of economic, social, and ecological systems. Based on the three subsystems of economic growth, social inclusion, and green sustainability, this study structures the indicator system of China’s inclusive green growth and reveals the characteristics of China’s inclusive green growth network using the social network analysis (SNA) method. Then, from the perspective of system deco

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Li, Yue Li, and Shu Hui Chang. "Research on Particle Swarm Optimsiation and its Application in Neural Network." Applied Mechanics and Materials 556-562 (May 2014): 5869–72. http://dx.doi.org/10.4028/www.scientific.net/amm.556-562.5869.

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This paper based on the PSO algorithm is a neural network model, and with other learning algorithm, and the results show that the performance comparisons are based on improved PSO algorithm two perceptron networks have higher classification accuracy and strong generalization ability. Particle Swarm Optimization (PSO) as an emerging evolutionary algorithm fast convergence speed, robustness, global search ability, and does not need the help of the characteristics of the problem itself (such as gradient). Combination of PSO and neural network PSO algorithm to optimize the connection weights of th

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Teguh Pradnyana Yoga, Gede, Gede Dyana Arjana, and I. Made Mataram. "PERBANDINGAN KOMBINASI FUNGSI PELATIHAN JARINGAN SYARAF TIRUAN BACKPROPAGATION PADA PERAMALAN BEBAN." Jurnal SPEKTRUM 7, no. 1 (2020): 41. http://dx.doi.org/10.24843/spektrum.2020.v07.i01.p6.

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Electricity system planning is very important for electricity providers (PLN). One of them is electricity load forecasting. Backpropagation artificial neural network is one of the best methods used in electricity load forecasting because it can give high accuracy values. In application, backpropagation neural networks often provide poor convergence speed values during the training process. Therefore, it is necessary to do various combinations of training functions to accelerate the convergence of network training. In this study, a backpropagation neural network model was developed with a combi

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Bai, Yonghua, Minzhou Luo, and Fenglin Pang. "An Algorithm for Solving Robot Inverse Kinematics Based on FOA Optimized BP Neural Network." Applied Sciences 11, no. 15 (2021): 7129. http://dx.doi.org/10.3390/app11157129.

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The solution of robot inverse kinematics has a direct impact on the control accuracy of the robot. Conventional inverse kinematics solution methods, such as numerical solution, algebraic solution, and geometric solution, have insufficient solution speed and solution accuracy, and the solution process is complicated. Due to the mapping ability of the neural network, the use of neural networks to solve robot inverse kinematics problems has attracted widespread attention. However, it has slow convergence speed and low accuracy. This paper proposes the FOA optimized BP neural network algorithm to

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Jónsson, Hlynur, Giovanni Cherubini, and Evangelos Eleftheriou. "Convergence Behavior of DNNs with Mutual-Information-Based Regularization." Entropy 22, no. 7 (2020): 727. http://dx.doi.org/10.3390/e22070727.

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Information theory concepts are leveraged with the goal of better understanding and improving Deep Neural Networks (DNNs). The information plane of neural networks describes the behavior during training of the mutual information at various depths between input/output and hidden-layer variables. Previous analysis revealed that most of the training epochs are spent on compressing the input, in some networks where finiteness of the mutual information can be established. However, the estimation of mutual information is nontrivial for high-dimensional continuous random variables. Therefore, the com

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Wang, Yu Jiao, Hai Yun Lin, and Hai Yan Li. "Study on Network Convergence Based on IMS Architecture." Advanced Materials Research 488-489 (March 2012): 1310–14. http://dx.doi.org/10.4028/www.scientific.net/amr.488-489.1310.

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As the core technology of next generation network, IMS supplies the standards and perfect methods to lay out the new service and converge between the traditional network and telephone and mobile network. IMS also provides the operators with a set of network system and new service means. Analyzing IMS system structure and combining the features of network convergence, this paper puts forward a network convergence plan based on IMS and fixed-mobile convergence.

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Zhong, Deyun, Liguan Wang, Jinmiao Wang, and Mingtao Jia. "An Efficient Mine Ventilation Solution Method Based on Minimum Independent Closed Loops." Energies 13, no. 22 (2020): 5862. http://dx.doi.org/10.3390/en13225862.

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In this paper, according to the analysis of optimum circuits, we present an efficient ventilation network solution based on minimum independent closed loops. Our main contribution is optimizing the circuit dividing strategy to improve the iteration convergence and the efficiency of a single iteration. In contrast to a traditional circuit, a minimum closed loop may contain one or more co-tree branches but fewer high-resistance branches and fan branches. It is helpful in solving the problem of divergence or slow convergence for complex ventilation networks. Moreover, we analyze the dividing rule

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Qu, Na, and Qinghui Wang. "Research on the Influence Mechanism of Media Convergence on the Improvement of Network Ideological and Political Education in Universities." Journal of Social Science Humanities and Literature 6, no. 6 (2023): 235–44. http://dx.doi.org/10.53469/jsshl.2023.06(06).35.

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From the perspective of media convergence, this paper systematically analyzes the influence mechanism of media convergence on network ideological and political education in universities, and the practical path of media convergence to boost network ideological and political education. This paper analyzes the influence mechanism of media convergence on network ideological and political education in universities from three aspects of communication mechanism, content form and technical means of media convergence. From three aspects: improving the system and mechanism, creating cultural characteris

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van Laarhoven, Karel, Ina Vertommen, and Peter van Thienen. "Technical note: Problem-specific variators in a genetic algorithm for the optimization of drinking water networks." Drinking Water Engineering and Science 11, no. 2 (2018): 101–5. http://dx.doi.org/10.5194/dwes-11-101-2018.

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Abstract. Genetic algorithms can be a powerful tool for the automated design of optimal drinking water distribution networks. Fast convergence of such algorithms is a crucial factor for successful practical implementation at the drinking water utility level. In this technical note, we therefore investigate the performance of a suite of genetic variators that was tailored to the optimization of a least-cost network design. Different combinations of the variators are tested in terms of convergence rate and the robustness of the results during optimization of the real-world drinking water distrib

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PARK, YOUNG-KEUN, and VLADIMIR CHERKASSKY. "NEURAL NETWORK FOR CONTROL OF REARRANGEABLE CLOS NETWORKS." International Journal of Neural Systems 05, no. 03 (1994): 195–205. http://dx.doi.org/10.1142/s0129065794000219.

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Rapid evolution in the field of communication networks requires high speed switching technologies. This involves a high degree of parallelism in switching control and routing performed at the hardware level. The multistage crossbar networks have always been attractive to switch designers. In this paper a neural network approach to controlling a three-stage Clos network in real time is proposed. This controller provides optimal routing of communication traffic requests on a call-by-call basis by rearranging existing connections, with a minimum length of rearrangement sequence so that a new bloc

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