2021 IEEE International Conference on Electronic Technology, Communication and Information (ICETCI)最新文献_第2页

User-transformer Relationship Verification Method of Low Voltage Distribution Network Based on Voltage Correlaion Analysis 基于电压相关性分析的低压配电网用户变压器关系验证方法

2021 IEEE International Conference on Electronic Technology, Communication and Information (ICETCI) Pub Date : 2021-08-27 DOI: 10.1109/ICETCI53161.2021.9563352

Jingming Zhao, Yongzhi Cai, Wenchong Guo, Jian Li

{"title":"User-transformer Relationship Verification Method of Low Voltage Distribution Network Based on Voltage Correlaion Analysis","authors":"Jingming Zhao, Yongzhi Cai, Wenchong Guo, Jian Li","doi":"10.1109/ICETCI53161.2021.9563352","DOIUrl":"https://doi.org/10.1109/ICETCI53161.2021.9563352","url":null,"abstract":"The accurate user-transformer relationship is essential to power loss analysis and outage management in low-voltage transformer area (LVTA). However, the traditional method like artificial investigation or momentary interruption is high cost, and the accuracy can not be guaranteed. Thus, an user-transformer relationship verification method of LVTA based on voltage correlation analysis is proposed. Firstly, the voltage characteristics of users which are in the correct and incorrect user-transformer relationship are analyzed, respectively. Secondly, an adaptive voltage clustering algorithm is proposed to presort the users. On this basis, the variance and average value of Pearson correlation coefficient (PCC) sequence of voltage time series between each users are calculated, which is used to judge whether the user is in the correct user-transformer relationship or not. Finally, the actual voltage data of two LVTAs are selected to verified the proposed method, and the results show that the proposed method can correctly identify the user-transformer relationship.","PeriodicalId":170858,"journal":{"name":"2021 IEEE International Conference on Electronic Technology, Communication and Information (ICETCI)","volume":"123 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133518250","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Attention-Based Bidirectional LSTM Network for Target Tracking 基于注意力的目标跟踪双向LSTM网络

2021 IEEE International Conference on Electronic Technology, Communication and Information (ICETCI) Pub Date : 2021-08-27 DOI: 10.1109/ICETCI53161.2021.9563583

Xinyu Yang, Dianfeng Qiao

{"title":"Attention-Based Bidirectional LSTM Network for Target Tracking","authors":"Xinyu Yang, Dianfeng Qiao","doi":"10.1109/ICETCI53161.2021.9563583","DOIUrl":"https://doi.org/10.1109/ICETCI53161.2021.9563583","url":null,"abstract":"One of the major challenges in target tracking is the inaccurate state estimation caused by motion uncertainty of the target. In this paper, a deep neural network-based method is proposed to fit the nonlinear mapping relationship between the filtering state, the measurement, and the real state to achieve effective tracking of the maneuvering trajectory. First, the encoder method is used to mine the favorable information in the target state and radar observation. Next, the bidirectional long short-term memory network (BI-LSTM) is used to memorize and fit the potential laws of the target motion. Then, the attention mechanism is introduced to make the network automatically capture the importance of the trajectory sequence, which greatly improves the efficiency and accuracy of estimation. Finally, we use decoder method to map the complicated functions between the estimated trajectory and the real trajectory. The simulation results verify that our attention-based bidirectional LSTM (ATBI-LSTM) method has a higher estimation accuracy and better dynamic performance than traditional algorithms without prior knowledge and a complex parameter adjustment process.","PeriodicalId":170858,"journal":{"name":"2021 IEEE International Conference on Electronic Technology, Communication and Information (ICETCI)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132173168","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Multi-Focus Image Fusion Based on Non-Subsampled Shearlet Transform and Consistency Optimization 基于非下采样Shearlet变换和一致性优化的多焦点图像融合

2021 IEEE International Conference on Electronic Technology, Communication and Information (ICETCI) Pub Date : 2021-08-27 DOI: 10.1109/ICETCI53161.2021.9563265

Xuejun Liu, Guanjun Wang, Fei Zhao

{"title":"Multi-Focus Image Fusion Based on Non-Subsampled Shearlet Transform and Consistency Optimization","authors":"Xuejun Liu, Guanjun Wang, Fei Zhao","doi":"10.1109/ICETCI53161.2021.9563265","DOIUrl":"https://doi.org/10.1109/ICETCI53161.2021.9563265","url":null,"abstract":"Aiming at the problems of information richness and insufficient edge definition of multi-focus fusion images, this paper proposes a multi-focus image fusion algorithm based on non-subsampled shear wave transform (NSST) and consistent optimization strategy. Firstly, the source image is decomposed by NSST transform in multi-scale and multi-direction to obtain high and low frequency subband coefficients. Secondly, Locally improved Laplacian energy and spatial consistency optimization strategy are used for low-frequency subband coefficients to construct low-frequency subband coefficient fusion weights; for high-frequency subband coefficients, spatial frequency and energy based on correlation coefficients are used, and phase consistency optimization is used. The strategy is to construct high-frequency sub-band coefficient fusion weights; finally, the final fusion image is obtained through NSST inverse transformation. The experimental results show that the proposed algorithm can improve the information retention and visual clarity of the fused image, whether in subjective vision or in objective evaluation.","PeriodicalId":170858,"journal":{"name":"2021 IEEE International Conference on Electronic Technology, Communication and Information (ICETCI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115380507","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Design of Distributed Cache System in SDN Controller Cluster Based on Topology Partition 基于拓扑划分的SDN控制器集群分布式缓存系统设计

2021 IEEE International Conference on Electronic Technology, Communication and Information (ICETCI) Pub Date : 2021-08-27 DOI: 10.1109/ICETCI53161.2021.9563459

Wei Jiang, Fei Xia, Hui Liu, Jun Yu

引用次数: 0

Mongolian Vowels in Non-initial Syllables and the Phonological Rules 蒙古语非声母音节中的元音及其语音规则

2021 IEEE International Conference on Electronic Technology, Communication and Information (ICETCI) Pub Date : 2021-08-27 DOI: 10.1109/ICETCI53161.2021.9563517

Yin Bao

引用次数: 0

Research on the Transmission Optimization Schemes of User Side Power Consumption Information 用户侧用电信息传输优化方案研究

2021 IEEE International Conference on Electronic Technology, Communication and Information (ICETCI) Pub Date : 2021-08-27 DOI: 10.1109/ICETCI53161.2021.9563447

Wu Zhongxing, Wang Chaoliang, Li Dan, Zhu Enguo, Zhu Zixu

引用次数: 0

Implementation of Numbered Head Together Learning Model for Improve Learning Achievement 实施编号Head Together学习模式提高学习成绩

2021 IEEE International Conference on Electronic Technology, Communication and Information (ICETCI) Pub Date : 2021-08-27 DOI: 10.1109/ICETCI53161.2021.9563511

Meiryani, An-Hwa Chang, A. Zudana, Zaidi Mat Daud

引用次数: 0

A review of structural improvements and applications of miniaturized ultra-precision motors 小型化超精密电机的结构改进与应用综述

2021 IEEE International Conference on Electronic Technology, Communication and Information (ICETCI) Pub Date : 2021-08-27 DOI: 10.1109/ICETCI53161.2021.9563585

Yunze Huang, Liqiang Wang, Xue Bai

引用次数: 0

The design and implementation of an automatic platform to screen chips 设计并实现了一个芯片自动筛选平台

2021 IEEE International Conference on Electronic Technology, Communication and Information (ICETCI) Pub Date : 2021-08-27 DOI: 10.1109/ICETCI53161.2021.9563402

Huang Guihua, Tian Liwei, Z. Tingting

引用次数: 0

High-dynamic adaptive geographic routing protocol based on topology for Smart Clusters 基于拓扑的智能集群高动态自适应地理路由协议

2021 IEEE International Conference on Electronic Technology, Communication and Information (ICETCI) Pub Date : 2021-08-27 DOI: 10.1109/ICETCI53161.2021.9563386

Huang Jinke, Zhao Xiaolin, Liang Weilong

引用次数: 0