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检索条件"任意字段=3rd Euro-NF Conference on Network Control and Optimization"

共 1644 条记录，以下是551-560 订阅

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2021 3rd International conference on Advanced Information Science and System, AISS 2021 - conference Proceedings

2021 3rd International Conference on Advanced Information Sc...

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3rd International conference on Advanced Information Science and System, AISS 2021

ISBN: (纸本)9781450385862

The proceedings contain 90 papers. The topics discussed include: University of Santo Tomas department of Filipino virtual front desk;comparison of the proportional hazard model and the accelerated failure model in the mixed cure model;radar working mode recognition method based on complex network analysis;facial expression recognition based on deep learning and attention mechanism;commercial aircraft on-board loadable software distribution and control digital solution;few-shot adversarial audio driving talking face generation;immune optimization algorithm for traveling salesman problem based on clustering analysis and self-circulation;and research on intelligent operational assisted decision-making of naval battlefield based on deep reinforcement learning.

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2020 3rd International Symposium on Traffic Transportation and Civil Architecture

2020 3rd International Symposium on Traffic Transportation a...

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2020 3rd International Symposium on Traffic Transportation and Civil Architecture, ISTTCA 2020

The proceedings contain 124 papers. The topics discussed include: impacts of drivers' physiological and psychological characteristics on road traffic safety based on traffic safety management database;urban parking scheme in Hangzhou based on reinforcement learning;research on eco-driving of signalized intersection fleet in vehicle-road cooperative environment;collaborative optimization for location-inventory problem of commercial vehicle distribution network;a comprehensive importance assessment method of high-speed railway network: a case study in China;passenger flow control method for network-wide operation of urban rail transit system: a case study in Guangzhou;and research on short-time prediction of driving behavior at unsignalized intersections based on machine learning.

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The flexible resource optimization scheduling considering the substation of the distribution network and the classification characteristics of electric vehicles

The flexible resource optimization scheduling considering th...

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Energy, Power and Electrical Technology (ICEPET), International conference on

作者： Busheng Luo Zhichao Lin Haohan Zhou Huizhou Power Supply Bureau Guangdong Power Grid Co. Ltd. Huizhou China Beijing Kedong Electric Power Control System Co. Ltd Beijing China

ISBN: (数字)9798350352658

ISBN: (纸本)9798350352665

Aiming at the deepening differentiation of distribution network areas and the flexible changes of electric vehicle resources, a flexible resource scheduling model considering the functional partitioning of active distribution networks and the classification characteristics of EVs is proposed. Firstly, an EV classification initialization model is established, categorizing charging periods and durations for private cars, taxis, and buses as examples. The EV charging and discharging are guided by congestion and willingness indices, and a regional controllable load model is built. Secondly, a spatiotemporal hierarchical scheduling model for the distribution network is constructed to minimize user costs and integrate renewable energy sources while scheduling flexible resources. At the lower level, an economic dispatch of EV charging and discharging locations and controllable loads in different areas is conducted. Finally, using the IEEE 33-node system as an example, simulations demonstrate that the proposed method can optimize the charging and discharging modes of various types of electric vehicles, thereby validating the effectiveness and rationality of the proposed approach.

关键词： Renewable energy sources Substations Distribution networks Electric vehicle charging Spatiotemporal phenomena Automobiles Resource management

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Key Node Identification of the Automotive Supply Chain network Based on Improved AFSA

Key Node Identification of the Automotive Supply Chain Netwo...

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networking Systems of AI (INSAI), International conference on

作者： Chengyang Ou Fubin Pan Minwei Chen Shuangjiao Lin Xiamen University of Technology Xiamen China Xiamen Huaxia University Xiamen China

ISBN: (数字)9798350344660

ISBN: (纸本)9798350344677

In the context of supply chain globalization, this paper applies complex network theory to construct automotive supply chain networks. The fundamental characteristics of the automotive supply chain are examined, and an improved artificial fish swarm algorithm-based key node identification method is proposed to address the limitations of existing approaches for complex networks. Following optimization and enhancement, the identification results are tested using the vandalism resistance of the automotive supply chain network as a metric. The analysis of the results reveals that the key nodes with the most significant impact on risk propagation in the automotive supply chain network are primarily the core automotive manufacturing enterprises, with certain auto parts enterprises also playing a crucial role. The proposed key node identification method offers a more intuitive means of identifying potential key risk control nodes within the automotive supply chain network, with valuable practical applications for preventing risk propagation in the automotive supply chain.

关键词： Resistance Measurement Supply chains Globalization Complex networks Fish Manufacturing Artificial intelligence optimization Automotive engineering

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Research on H∞ preview control algorithm for industrial wireless sensor networks 3

Research on H∞ preview control algorithm for industrial wir...

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2021 3rd International conference on Artificial Intelligence and Computer Science, AICS 2021

作者： Shi, Yuanbo Huang, Yueyang Hou, Shaojing Wu, Yinghao School of Computer and Communication Engineering Liaoning Petrochemical University Fushun Liaoning 113001 China School of Information and Control Engineering Liaoning Petrochemical University Liaoning Fushun113001 China

In order to solve the problem of wireless sensor network control system with network delay and packet loss, a H∞ preview control algorithm is designed. Firstly, the wireless sensor network model with delay and packet loss is established, and the system error and predictable target signal are introduced to construct the extended error system. Secondly, the state feedback controller with memory is designed. By constructing Lyapunov function and linear matrix inequality, the design method of H∞ controller and the sufficient conditions for the stability of the system are derived. The optimal H∞ preview controller algorithm is obtained by solving the LMI optimization problem. Finally, the effectiveness of H∞ preview controller algorithm is verified by simulation. © Journal of Physics: conference Series 2021.

关键词： controllers

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Optimal Split Bearer control and Resource Allocation for Multi-Connectivity in 5G New Radio 30

Optimal Split Bearer Control and Resource Allocation for Mul...

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Joint 30th european conference on networks and Communications / 3rd 6G Summit (EuCNC/6G Summit)

作者： Elias, Jocelyne Martignon, Fabio Paris, Stefano Univ Bologna Bologna Italy Univ Bergamo Bergamo Italy Nokia Bell Labs Turin Italy

ISBN: (纸本)9781665415262

Wireless cellular systems are evolving towards the integration of services and devices with a diverse set of throughput, latency, and reliability requirements. To this end, 3GPP has introduced Multi Connectivity (MC) as a more flexible architecture for 5G NR (New Radio), where multiple wireless connections can be used simultaneously to split or duplicate data traffic. While multi connectivity improves single user performance, the inherent increase of data transmissions on the wireless channel may result in higher interference, thus reducing the overall system performance. This paper analyzes the problem of admission control and resource allocation in multi connectivity scenarios, considering different requirements and 5G NR features. We formulate the problem as an optimization program and provide an heuristic approach to solve it. Numerical results in a realistic network deployment confirm that our solution can effectively allocate radio resources in order to increase admission rate and system throughput.

关键词： 5G Multi-Connectivity Split-Bearer optimization

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Analysis of the Behavior of a Standalone PV System Based on Classical and Advanced MPPT Algorithms

Analysis of the Behavior of a Standalone PV System Based on ...

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International conference on Advanced Electrical Engineering (ICAEE)

作者： Meriem Farou Abdelhak Djellad Sofiane Chiheb Hala Lalaymia Nacer Bouderess ENSTI LTSE Laboratory National Higher School of Technology and Engineering Annaba Algeria Department of Electrical Engineering Brothers Mentouri University Constantine Algeria

ISBN: (数字)9798350349351

ISBN: (纸本)9798350349368

Over the last few years, several control methods for Maximum Power Point Tracking (MPPT) of Photovoltaic (PV) systems have been developed to ensure that the solar cells operate at their maximum power point under varying conditions as the temperature and irradiance change. The work of this paper is dedicated to a comprehensive comparative analysis of both classical: Incremental Conductance (InC), Perturb and Observe (P&O), Hill climbing (HC), and advanced: Fuzzy Logic control (FLC), Artificial Neural network (ANN), Particle Swarm optimization (PSO) MPPT algorithms, all of them have been created for PV system and simulated to obtain the various system responses such as the power and the voltage on Direct Current (DC) load. The results of the simulation tests confirmed that the algorithm based on ANN has the fastest response time; the respective stability percentages of HC, FLC, ANN, P&O, InC, and PSO were found to be 76%, 88.9%, 96.9%, 97.03%, 97.05%, and 97.5%.

关键词： Maximum power point trackers Temperature dependence Simulation Artificial neural networks Thermal management Stability analysis Temperature control Time factors Voltage control Thermal stability

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Accelerating 5G Service-Based Architecture with Ebpf 23

Accelerating 5G Service-Based Architecture with Ebpf

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Proceedings of the 2023 12th International conference on networks, Communication and Computing

作者： Yong Xuan Huang Kung Chun Wang Bi Shun Ke Chunghwa Telecom Laboratories Taiwan

ISBN: (纸本)9798400709265

Service-Based Architecture (SBA) serves as a foundational methodology for 5G core networks, as delineated by the 3rd Generation Partnership Project (3GPP). This modular approach segments the 5G Core network into discrete, functionally autonomous network Functions (nfs), deployed via either virtual machines or container technologies. The efficacy of the SBA execution platform significantly impacts the service capabilities of these nfs. In this study, we present an enhanced architecture that employs extended Berkeley Packet Filter (eBPF) and eXpress Data Path (XDP) technologies to fine-tune the network, security, service, and scheduling aspects within a Kubernetes framework. Additionally, eBPF’s monitoring and packet control features augment the service capabilities of 5G components, thereby improving encrypted data transmission. eBPF’s real-time monitoring aids the scheduler in making nuanced decisions, while an eBPF-driven load balancer ensures equitable service distribution. Comprehensive testing reveals that the enhanced architecture increases transmission efficiency by 17%, reduces average latency by 43%, and alleviates latency anomalies compared to conventional 5G nf platforms. It also enhances the inherent connectivity of 5G nfs by approximately 15%. For encryption-reliant applications, the architecture achieves a 17% performance gain in latency, transmission, and connectivity, while its scheduling and service balancing capabilities demonstrate a roughly 19% performance enhancement.

关键词： 5G Core network Virtual network Acceleration eBPF/XDP

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Strategies for network Traffic optimization: An In-Depth Analysis of Multipath Routing Algorithms in SDN

Strategies for Network Traffic Optimization: An In-Depth Ana...

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Mobile networks and Wireless Communications (ICMNWC), IEEE International conference on

作者： Venkata Sai. R Prabu. U Satwik. Ch Sanjaya Kumar Panda V. Geetha Department of CSE Velagapudi Ramakrishna Siddhartha Engineering College Vijayawada India Department of CSE National Institute of Technology Warangal India Department of Information Technology Puducherry Technological University Puducherry India

Demand for online services and cloud services has been increasing day to day. The usage of these services increases network traffic, which is difficult to handle by traditional networks. In the traditional networking paradigm, it is very difficult to integrate various networking devices of different versions. The programming capability in traditional networks is very less which requires manual installation even for small changes in the network. The traditional networking paradigm is a distributed architecture, in which individual networking devices will take control of the network devices which are under them. Overcoming the above limitations, a new networking paradigm called Software Defined networking (SDN) came into existence. SDN possesses a centralized architecture in which the controller will take all the routing decisions and those instructions will be forwarded to the forwarding elements called switches. Through programming, networking devices can be configured which reduces manual installation. In this article, a detailed study on multipath routing in SDN is done. It provides a detailed study regarding different ways of implementing multipath routing. Multipath routing based on optimization techniques and machine learning techniques are discussed. This chapter consists description of how load balancing can be improved and how Quality of Service (QoS) can be improved using multipath routing. Multipath routing using shortest path algorithms like the Bellman-Ford algorithm, and Depth First Search (DFS) are discussed and how deep neural networks and reinforcement learning mechanisms will be used to implement multipath routing and to improve network performance is discussed. This study helps other researchers who try to do research based on multipath routing over SDN to get an overview of multipath routing.

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The Dynamics of Gradient Descent for Overparametrized Neural networks 3

The Dynamics of Gradient Descent for Overparametrized Neural...

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3rd Annual conference on Learning for Dynamics and control (L4DC)

作者： Satpathi, Siddhartha Srikant, R. Univ Illinois Dept Elect & Comp Engn Urbana IL 61801 USA

We consider the dynamics of gradient descent (GD) in overparameterized single hidden layer neural networks with a squared loss function. Recently, it has been shown that, under some conditions, the parameter values obtained using GD achieve zero training error and generalize well if the initial conditions are chosen appropriately. Here, through a Lyapunov analysis, we show that the dynamics of neural network weights under GD converge to a point which is close to the minimum norm solution subject to the condition that there is no training error when using the linear approximation to the neural network. To illustrate the application of this result, we show that the GD converges to a prediction function that generalizes well, thereby providing an alternative proof of the generalization results in Arora et al. (2019).

关键词： Overparametrized Neural network Neural Tangent Kernel Gradient Descent

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