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network configuration Entity Extraction Method Based on Transformer with Multi-Head Attention Mechanism

Computers, Materials & Continua 2024年第1期78卷 735-757页

作者： Yang Yang Zhenying Qu Zefan Yan Zhipeng Gao Ti Wang State Key Laboratory of networking and Switching Technology Beijing University of Posts and TelecommunicationsBeijing100876China Product Development Department China Unicom Smart City Research InstituteBeijing100044China

Nowadays,ensuring thequality of networkserviceshas become increasingly *** are turning toknowledge graph technology,with a significant emphasis on entity extraction in the identification of device *** research paper presents a novel entity extraction method that leverages a combination of active learning and attention ***,an improved active learning approach is employed to select the most valuable unlabeled samples,which are subsequently submitted for expert *** approach successfully addresses the problems of isolated points and sample redundancy within the network configuration sample *** the labeled samples are utilized to train the model for network configuration entity ***,the multi-head self-attention of the transformer model is enhanced by introducing the Adaptive Weighting method based on the Laplace mixture *** enhancement enables the transformer model to dynamically adapt its focus to words in various positions,displaying exceptional adaptability to abnormal data and further elevating the accuracy of the proposed *** comparisons with Random Sampling(RANDOM),Maximum Normalized Log-Probability(MNLP),Least Confidence(LC),Token Entrop(TE),and Entropy Query by Bagging(EQB),the proposed method,Entropy Query by Bagging and Maximum Influence Active Learning(EQBMIAL),achieves comparable performance with only 40% of the samples on both datasets,while other algorithms require 50% of the ***,the entity extraction algorithm with the Adaptive Weighted Multi-head Attention mechanism(AW-MHA)is compared with BILSTM-CRF,Mutil_Attention-Bilstm-Crf,Deep_Neural_Model_NER and BERT_Transformer,achieving precision rates of 75.98% and 98.32% on the two datasets,*** tests demonstrate the statistical significance and effectiveness of the proposed algorithms in this paper.

关键词： Entity extraction network configuration knowledge graph active learning transformer

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Research on network configuration and Voltage Control of DC Distribution Station

Research on Network Configuration and Voltage Control of DC ...

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第三十九届中国控制会议

作者： Fuwen Su Dan Wang Chengxiong Mao Ziliu Ye School of Computer Science and Technology Wuhan University of Technology School of Electrical and Electronic Engineering Huazhong University of Science and Technology School of Automation Wuhan University of Technology

With the rapid development of distributed energy, the power grid, especially the urban power grid, is facing many challenges. In this paper, the concept of DC distribution station is proposed. As a key component of DC distribution system, DC distribution station will play the advantages of DC distribution technology to promote the transformation of traditional urban power grid into a new urban power grid. A reasonable overall topology is proposed, and the appropriate voltage control strategy is selected. Besides, the simulation model of DC distribution station is built in MATLAB/SIMULINK. The simulation under steady-state condition verifies the feasibility of the DC distribution station and the correctness of the control strategy.

关键词： DC distribution station network configuration voltage control DC distribution network

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Research on Communication network configuration and Simulation of Smart Substation Based on Ethernet

Research on Communication Network Configuration and Simulati...

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作者： Jingxia Liu Xuerang Zhang Fuquan Zhang College of Information Engineering Inner Mongolia University of Science ＆ Technology

The characters of the intelligent substation communication network structure are analyzed in the paper. Combining existing integrated automation substation hardware circuit and VLAN（Virtual Local Area network） research foundation to optimize the network configuration. In accordance with IEC61850 standard, the network is partitioned into several VLANs based on the Tag VLAN division method of ID address. Real-time communication packets between GOOSE networks, SV（sampling information） networks, and switches use 802.1 Q protocol headers to distinguish these packets. Finally, OPNET simulation software was used to simulate and verify the simplified dual-star topology. The results demonstrate that the delay and traffic bandwidth meet the requirements of actual substation operation standards. Compared with ordinary single-star networks, the reliability is greatly improved and the effectiveness is improved.

关键词： Intelligent Substation network configuration VLAN Division GOOSE and SV OPNET

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Impact of the Objective Function on the Construction of Internal Grids of Wind Farms Using Genetic Algorithm

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Open Journal of Civil Engineering 2016年第5期6卷 705-721页

作者： Paulo R. Monteiro Duailibe Thiago T. Borges André F. Schiochet Carlos Alberto P. Soares Programa de Pós-Graduaç ã o em Engenharia Civil Universidade Federal Fluminenese Niterói Brasil Departamento de Engenharia Elétrica Universidade Federal Fluminense Niterói Brasil Petróleo Brasileiro S/A Rio de Janeiro Brasil

The macro complex of the construction industry is energy intensive. Solutions that enable the supply of this demand while meeting the principles of sustainability are needed. The construction of wind farms has been a strategy employed by many countries to produce clean energy. An increase in the construction of wind farms has also been witnessed in Brazil. This calls for different activities, such as the design and construction of infrastructure. This article focuses on the design of internal medium voltage distribution grids for wind farms. The purpose is to find a radial configuration that connects a set of wind generators to the substation, in an optimum way, minimizing operational and construction costs, reducing loss and therefore contributing to sustainability. In large farms, the project design consists of a large combinatorial optimization problem, given the large number of possible configurations to be deployed. Finding the best solution for the internal grid depends on the criterion adopted for the objectives pursued. This article analyzes the different criteria that can be adopted in the design of the wind farm’s internal grid using a methodology based on genetic algorithm (GA). Its aim is to identify their influence on the solution of the problem and help decision-making by finding the most adequate criterion for the objectives pursued. The results show that the design of the internal grid is sensitive to the criteria adopted for the objective function. In addition, the degree of sensitivity is analyzed, showing that, in some cases, the solutions are not economically attractive and do not contribute to the reduction of losses.

关键词： Construction Infrastructure Wind Farm Infrastructure Collection Grid network configuration Genetic Algorithm

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Reasearch on improving coal mine tremor location accuracy

Reasearch on improving coal mine tremor location accuracy

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2014年中国地球科学联合学术年会——国际专题（2）M...

作者： Gong Si-yuan DOU Lin-ming CAO An-ye WANG Gui-feng HE Hu HE Jiang State Key Laboratory of Coal Resource and Safe Mining China University of Mining & Technology School of Mines China University of Mining & Technology

The rockburst phenomenon caused mostly by mining-induced tremors becomes progressively more severe as the mining depth and extent increase. Microseismic monitoring technique, as the major investigation tool for the monitoring of rockburst and other mining dynamic hazards, has been widely used in many coal mines around the world. To ensure the accuracy of seismic source locating and energy calculation, and further improve the feasibility of rockburst forecasting, an optimal design and assessment system of tremor location needs to be built first. In this paper, according to practical conditions and requirements of coal mines, especially the accuracy of picking seismic wave arrivals at stations and building velocity model, the main influencing factors and bad conditions which influence the accuracy of source location were analyzed using the theory of D-optimal design and localization, then the optimal design and assessment system of network was built up. For optimizing the large-scale network configuration of combinatorial optimization problem, a model, including the blocks of input data preparation,genetic algorithm and location capability assessment of network,is constructed to solve the establishment of optimal objective function of microseismic network layout. According to the characteristics of layer bedding strata and bedseparation zone in coal mine, and anisotropic velocity model is built by two kinds of velocity, that is, one for underground sensor and the other for surface sensor, to form the velocity vector. Based on the practical conditions of coal mine and the characteristics of propagation of seismic wave, a principle is build to choose the optimal channel numbers, and for evaluation of location accuracy, two variance functions in the evaluation model are constructed to describe the increased fluctuations of P wave velocity and the marked first arrival time with the increase of distance between source and station, P wave amplitude damping coefficient and c

关键词： Microseismic observation system network configuration Anisotropic velocity model Genetic algorithm Optimal channel numbers

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