Electric vehicles(EVs)are widely deployed throughout the world,and photovoltaic(PV)charging stations have emerged for satisfying the charging demands of EV *** paper proposes a multi-objective optimal operation method...
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Electric vehicles(EVs)are widely deployed throughout the world,and photovoltaic(PV)charging stations have emerged for satisfying the charging demands of EV *** paper proposes a multi-objective optimal operation method for the centralized battery swap charging system(CBSCS),in order to enhance the economic efficiency while reducing its adverse effects on power *** proposed method involves a multi-objective optimization scheduling model,which minimizes the total operation cost and smoothes load fluctuations,***,we modify a recently proposed multi-objective optimization algorithm of non-sorting genetic algorithm III(NSGA-III)for solving this scheduling ***,simulation studies verify the effectiveness of the proposed multi-objective operation method.
As the scale of micro-service systems on the cloud continues to expand, the dependencies between micro-services become more and more complex. Service anomalies may continue to propagate with the call relationship, lea...
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Owing to the wide application of lithium-ion batteries in industry, it is of great significance for accurate prediction of battery state of health (SOH) to ensure the safety and stability of equipment. The battery cap...
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Femtocell network has a great development space in increasing coverage and capacity of wireless network. In order to meet the quality of service (QoS) requirements of MUEs in MBS coverage, we propose a seed channel in...
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Multi-agent technology is widely used in many fields such as intelligent manufacturing, logistics and environment exploration. In this paper, we propose a greedy K-means self-organizing map algorithm to balance the ta...
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Federated learning (FL) is a promising distributed machine learning technique for solving the privacy leakage problem in machine learning training process. Multiple parties collaborate to train a machine learning mode...
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The globalization of hardware designs and supply chains,as well as the integration of third-party intellectual property(IP)cores,has led to an increased focus from malicious attackers on computing ***,existing defense...
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The globalization of hardware designs and supply chains,as well as the integration of third-party intellectual property(IP)cores,has led to an increased focus from malicious attackers on computing ***,existing defense or detection approaches often require additional circuitry to perform security verification,and are thus constrained by time and resource *** the scale of actual engineering tasks and tight project schedules,it is usually difficult to implement designs for all modules in field programmable gate array(FPGA)*** studies have pointed out that the failure of key modules tends to cause greater damage to the ***,under limited conditions,priority protection designs need to be made on key modules to improve protection *** have conducted research on FPGA designs including single FPGA systems and multi-FPGA systems,to identify key modules in FPGA *** the single FPGA designs,considering the topological structure,network characteristics,and directionality of FPGA designs,we propose a node importance evaluationmethod based on the technique for order preference by similarity to an ideal solution(TOPSIS)***,for the multi-FPGA designs,considering the influence of nodes in intra-layer and inter-layers,they are constructed into the interdependent network,and we propose a method based on connection strength to identify the important ***,we conduct empirical research using actual FPGA designs as *** results indicate that compared to other traditional indexes,node importance indexes proposed for different designs can better characterize the importance of nodes.
Deploying reconfigurable intelligent surfaces (RIS) in vehicular networks can effectively improve the quality of wireless channel and increase network throughout, which is realized by optimizing the phase shifters. Ho...
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Semi-supervised learning (SSL) is a successful paradigm that can use unlabelled data to alleviate the labelling cost problem in supervised learning. However, the excellent performance brought by SSL does not transfer ...
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Currently, the dominant encoding method for computer-generated holograms is phase-only holography. The Gerchberg-Saxton (GS) algorithm is a commonly used approach for hologram generation. However, it suffers from issu...
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