2022 IEEE 6th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC )最新文献

An intelligent measuring device and its function realization method for deepening application in substation 一种智能测量装置及其功能实现方法在变电站的深入应用

2022 IEEE 6th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC ) Pub Date : 2022-10-03 DOI: 10.1109/IAEAC54830.2022.9929732

Jun Du, Lin Fan, Yongxu Cui, Hua Liang, Yongfu Liu

引用次数: 1

Pedestrian fall detection based on AC-YOLOv5s 基于AC-YOLOv5s的行人跌倒检测

2022 IEEE 6th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC ) Pub Date : 2022-10-03 DOI: 10.1109/IAEAC54830.2022.9929889

Guoxin Shen, Ziqin Wei, Xuerong Li, Yi Wei, Ke Li

引用次数: 0

Mobile Perimeter Guard System based on Deep Convolutional Neural Networks 基于深度卷积神经网络的移动周界警戒系统

2022 IEEE 6th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC ) Pub Date : 2022-10-03 DOI: 10.1109/IAEAC54830.2022.9929575

Zhixiang Yang, Wanhua Cao, Jiarui Hu, Quan Li, Haochen Liu

引用次数: 0

The Low-light Image Enhancement Method Based on Improved LSID Algorithm 基于改进LSID算法的弱光图像增强方法

2022 IEEE 6th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC ) Pub Date : 2022-10-03 DOI: 10.1109/IAEAC54830.2022.9929796

Jinbao Yang, Zhimin Yuan, Shilei Li, Jiasheng Wang

引用次数: 0

Deep-Learning-Based Localization Approach with Pseudorange for Pseudolite Systems 基于深度学习的伪卫星系统伪距定位方法

2022 IEEE 6th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC ) Pub Date : 2022-10-03 DOI: 10.1109/IAEAC54830.2022.9929978

Runlong Ouyang, Xiye Guo, Jun Yang, Kai Liu, Zhiiun Meng, Xiaoyu Li, Guokai Chen, Suyang Liu

{"title":"Deep-Learning-Based Localization Approach with Pseudorange for Pseudolite Systems","authors":"Runlong Ouyang, Xiye Guo, Jun Yang, Kai Liu, Zhiiun Meng, Xiaoyu Li, Guokai Chen, Suyang Liu","doi":"10.1109/IAEAC54830.2022.9929978","DOIUrl":"https://doi.org/10.1109/IAEAC54830.2022.9929978","url":null,"abstract":"The pseudolite system can broadcast navigation signals and can be used as a good supplement or substitute to the global navigation satellite systems. The pseudorange measurement is usually used to calculate the initial position. However, the pseudorange positioning is still faced with the multipath problem. To improve the positioning accuracy, a deep-learning localization method is proposed in this paper. The proposed method mainly includes the offline initial phase and the online localization phase. During the offline phase, the pseudorange data is collected and transformed into single-differenced pseudorange. The database is expanded by copying the pseudorange vectors and masking pseudorange values. Then a residual fully connected neural network (ResFCNN) is used to learn the mapping relationship between single-differenced pseudorange and location. A residual connection across fully connected layers is added in the ResFCNN to strengthen the learning ability of neural networks. During the online phase, the trained model and real-time pseudoranges are used to predict the location. Experimental results show that the root-mean-square error (RMSE) of the proposed method is 0.73 m under a multipath condition and 1.21 m with a signal absence, which are reductions in RMSE of 81 and 85%, respectively, compared to the conventional iterative least squares method.","PeriodicalId":349113,"journal":{"name":"2022 IEEE 6th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC )","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126143366","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: 0

Research on Load-Bearing Quality Evaluation Method of 5G Network for Power Business 电力业务 5G 网络承载质量评估方法研究

2022 IEEE 6th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC ) Pub Date : 2022-10-03 DOI: 10.1109/IAEAC54830.2022.9929900

Jinjiang Tang, Weijun Zheng, Yanming Gao, Zheng Wang, Hao Zhou, Jiming Yao

{"title":"Research on Load-Bearing Quality Evaluation Method of 5G Network for Power Business","authors":"Jinjiang Tang, Weijun Zheng, Yanming Gao, Zheng Wang, Hao Zhou, Jiming Yao","doi":"10.1109/IAEAC54830.2022.9929900","DOIUrl":"https://doi.org/10.1109/IAEAC54830.2022.9929900","url":null,"abstract":"In view of the problem that the highway network measurement system cannot accurately evaluate the load-bearing quality of electric power business, a quantitative evaluation method of 5G network quality for electric power business is proposed, and a four-level composite weighted evaluation model of 5G network bearing quality of electric power business is constructed. The wireless network quality evaluation index system is established, which covers the key performance indicators of all kinds of electric power business. The quantitative evaluation method of service bearing quality is proposed and realized systematically. The system supports power business simulation, terminal signal quality, end-to-end delay, reliability and other test capabilities. It has the functions of power multi-service carrying quality evaluation, comparison of 5G multi-network test results, and test analysis of key indicators of 5G network. It can accurately judge the network quality of the business side, scientifically evaluate and verify the service quality of 5G network carrying power business, make up for the shortcomings of the traditional road-oriented network test system, and quickly locate the problem, which plays an important role in the operation, maintenance and optimization of power 5G network slices.","PeriodicalId":349113,"journal":{"name":"2022 IEEE 6th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC )","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126654811","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: 0

Situation Assessment based on Dissimilarity Calculation and Evidence Combination 基于不相似度计算和证据组合的态势评估

2022 IEEE 6th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC ) Pub Date : 2022-10-03 DOI: 10.1109/IAEAC54830.2022.9929952

Yongwei Wang, Huifang Su, Yuchen Zhang, Yifei Wang, Shengnan Zhou, P. Liu

引用次数: 0

Simulation study on battery performance of APU emergency starting under multiple states APU多状态紧急起动电池性能仿真研究

2022 IEEE 6th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC ) Pub Date : 2022-10-03 DOI: 10.1109/IAEAC54830.2022.9929461

Yang Dongjin, Ding Qi

引用次数: 0

Wind power Prediction based on the fusion of CN N-GRU combined neural network and attention mechanism 基于CN - N-GRU联合神经网络与注意力机制融合的风电预测

2022 IEEE 6th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC ) Pub Date : 2022-10-03 DOI: 10.1109/IAEAC54830.2022.9929869

Yankun Wang, Zhenda Song, Yuchen Liu, Jiacheng Chen

引用次数: 0

Feature extraction of channel wave signal in coal seam based on phased source 基于相位源的煤层通道波信号特征提取

2022 IEEE 6th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC ) Pub Date : 2022-10-03 DOI: 10.1109/IAEAC54830.2022.9929538

Hongyu Sun, Xia Liu, Jiao Song, Jianuo Sun, Yu Chen

{"title":"Feature extraction of channel wave signal in coal seam based on phased source","authors":"Hongyu Sun, Xia Liu, Jiao Song, Jianuo Sun, Yu Chen","doi":"10.1109/IAEAC54830.2022.9929538","DOIUrl":"https://doi.org/10.1109/IAEAC54830.2022.9929538","url":null,"abstract":"When the channel wave propagates in the coal seam and encounters an abnormal structure, the frequency, amplitude and other parameters will change. Receiving the channel wave signal clearly and extracting the time-frequency characteristics accurately are the keys to predict the abnormal structure ahead. In this paper, the phased source and new feature extraction method were employed for channel wave seismic exploration. The controllable phased source is used to generate channel wave. The CEEMDAN algorithm based on the EMD algorithm and the Fast ICA algorithm for blind source signal separation are combined new Fast ICA-CEEMDAN method for decomposing the channel wave signal. The homogeneous medium and the equivalent medium model of the mined-out coal measure stratum are established by the COMSOL multiphysics, the received channel wave signal is decomposed by Fast ICA-CEEMDAN method. The Hilbert marginal spectrum, time spectrum, instantaneous frequency spectrum and instantaneous frequency spectrum of channel wave signal were extracted. There are five characteristic parameters of phase spectrum and instantaneous amplitude spectrum. The results show that the method can accurately reflect the local characteristics of the channel wave signal, and has high time-frequency resolution, which provides favorable reference for coal mining.","PeriodicalId":349113,"journal":{"name":"2022 IEEE 6th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC )","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116450892","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: 0