2021 IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers (IPEC)最新文献_第9页

Research on Intelligent Online Test System of Linear Algebra Based on Mathematical Modeling 基于数学建模的线性代数智能在线考试系统研究

2021 IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers (IPEC) Pub Date : 2021-04-14 DOI: 10.1109/IPEC51340.2021.9421096

Hanying Sun, Yujun Song

引用次数: 0

Reaserch on zigbee-based airborne wireless pressure test network 基于zigbee的机载无线压力测试网络研究

2021 IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers (IPEC) Pub Date : 2021-04-14 DOI: 10.1109/IPEC51340.2021.9421102

Yuqin Zhang, F. Yi, Panwen Li

引用次数: 0

Optimization for Satellite Navigation System Level Parameter Modelling Based on Artificial Neural Network 基于人工神经网络的卫星导航系统级参数建模优化

2021 IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers (IPEC) Pub Date : 2021-04-14 DOI: 10.1109/IPEC51340.2021.9421088

Z. Liu

{"title":"Optimization for Satellite Navigation System Level Parameter Modelling Based on Artificial Neural Network","authors":"Z. Liu","doi":"10.1109/IPEC51340.2021.9421088","DOIUrl":"https://doi.org/10.1109/IPEC51340.2021.9421088","url":null,"abstract":"BP algorithm is a common method to correct satellite navigation system level parameter modelling, which can significantly improve the accuracy of the measurement results. However, the traditional BP algorithm is easy to fall into local minimum, which makes the accuracy and stability of the measurement results poor. In this paper, an optimization algorithm based on immune algorithm and BP neural network is proposed. The global search is carried out by using the immune algorithm, and then the BP algorithm is used for local search. The experimental results show that the optimization algorithm can effectively avoid the traditional BP algorithm falling into local minimum when training multi-layer forward neural network, and has the merits of high prediction precision, rapid convergence, global superiority and accuracy for optimization. The measurement accuracy is improved. Moreover, the mean square error between the satellite navigation system height fitting error and the standard value of the neural network is less than 0.0422, the average error is less than 0.0466 and the maximum relative error is less than 0.0496.","PeriodicalId":340882,"journal":{"name":"2021 IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers (IPEC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124079930","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

Research on Parallel K-Nearest Neighbor Query Optimization Method for Highway Big Data 高速公路大数据并行k近邻查询优化方法研究

2021 IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers (IPEC) Pub Date : 2021-04-14 DOI: 10.1109/IPEC51340.2021.9421318

Min Li

{"title":"Research on Parallel K-Nearest Neighbor Query Optimization Method for Highway Big Data","authors":"Min Li","doi":"10.1109/IPEC51340.2021.9421318","DOIUrl":"https://doi.org/10.1109/IPEC51340.2021.9421318","url":null,"abstract":"Because the information in the field of engineering construction involves remote sensing recognition, intelligent transportation, etc. The rapid growth of various types of information makes highway data continue to develop toward the trend of big data in terms of scale, type, and structure, showing the characteristics of multi-source heterogeneous. This article discusses efficient data retrieval and query methods for specific highway basic databases and simulated highway spatial large data sets. In order to better manage spatial objects and maintain their positional relationship with grid cells, it is proposed to combine inverted index with grid index. In order to break the dependence of the rim radius on the previous traversal results, the serial rim access K nearest neighbor (KNN) algorithm is appropriately improved, and the rim radius is updated by increasing the mesh side length, combined with multi-threading technology Achieve access to multiple rims to improve the query performance of highway big data. Test data by modifying the size, spatial grid sides and these K values, the average performance are improved.","PeriodicalId":340882,"journal":{"name":"2021 IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers (IPEC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128744847","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

Modeling of Vehicle Driving Behavior in Tunnel Entrance Zone Based on Artificial Potential Field Theory 基于人工势场理论的隧道入口区车辆行驶行为建模

2021 IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers (IPEC) Pub Date : 2021-04-14 DOI: 10.1109/IPEC51340.2021.9421333

Xiao Yang

{"title":"Modeling of Vehicle Driving Behavior in Tunnel Entrance Zone Based on Artificial Potential Field Theory","authors":"Xiao Yang","doi":"10.1109/IPEC51340.2021.9421333","DOIUrl":"https://doi.org/10.1109/IPEC51340.2021.9421333","url":null,"abstract":"The special traffic rules and environmental factors in the entrance area of the tunnel increase the difficulty of modeling vehicle driving behavior. In response to this problem, this paper incorporates the speed limit, lane changing restrictions, and other traffic rules and tunnel environment on vehicle driving into the potential field model based on the traditional potential field theory. According to the characteristics of the tunnel entrance area, the vehicle potential field and the lane line potential field were improved respectively, and a new tunnel potential field was established. Besides, the relative velocity is introduced to establish an improved potential field force model. On this basis, the vehicle driving behavior model in the tunnel entrance zone is obtained by analyzing the improved artificial potential field(APF) model established. Besides, the driving simulator is used to collect the driving data of five drivers in the tunnel entrance zone, and the least square method and genetic algorithm are used to calibrate and verify the parameters of the improved artificial potential field. And the driving behavior model was verified through experiments. The results of driver-in-the-loop experiments show that the established vehicle driving behavior model can reveal the dynamic evolution of the driving behavior of vehicles in the tunnel entrance zone. It can provide a basis for the study of cooperative driving behavior of vehicles in the tunnel entrance zone and the driving decision-making research of driving assistance systems.","PeriodicalId":340882,"journal":{"name":"2021 IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers (IPEC)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122232787","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

Analysis of Intelligent Logistics Supply Chain Management under the Internet of Things 物联网下的智能物流供应链管理分析

2021 IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers (IPEC) Pub Date : 2021-04-14 DOI: 10.1109/IPEC51340.2021.9421218

Huiying Zhang

{"title":"Analysis of Intelligent Logistics Supply Chain Management under the Internet of Things","authors":"Huiying Zhang","doi":"10.1109/IPEC51340.2021.9421218","DOIUrl":"https://doi.org/10.1109/IPEC51340.2021.9421218","url":null,"abstract":"The Internet of Things technology continues to develop and popularize by the relentless march of technology, the application of the Internet of Things technology provides support for logistics supply chain management. The management level and efficiency of the supply chain determine the core competitiveness of the enterprise to a certain extent, Enterprises have higher and higher requirements for logistics supply chain management, therefore, the intelligent logistics supply chain management based on the Internet of Things emerges as the times require. At present, in the logistics supply chain of most enterprises, the speed of information transmission is very low, and information exchange errors often occur, which brings immeasurable losses to enterprises. For this reason, enterprises must strengthen the management work of intelligent logistics supply chain, should integrate the actual situation of the logistics supply chain, build the efficient logistics network with the help of the Internet of Things technology, and lay the foundation for the realization of intelligent management of the logistics supply chain. This paper analyzes and studies the management of intelligent logistics chain under the Internet of Things technology, and aims to promote the efficient development of logistics supply chain.","PeriodicalId":340882,"journal":{"name":"2021 IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers (IPEC)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130403464","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: 2

Research on the Construction and Application of Computer Financial Analysis System in Enterprises 企业计算机财务分析系统的构建与应用研究

2021 IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers (IPEC) Pub Date : 2021-04-14 DOI: 10.1109/IPEC51340.2021.9421255

Liu Yu

引用次数: 1

Research on Text Classification Method Based on LSTM Neural Network Model 基于LSTM神经网络模型的文本分类方法研究

2021 IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers (IPEC) Pub Date : 2021-04-14 DOI: 10.1109/IPEC51340.2021.9421225

Yanbo Zhang

引用次数: 5

Research on Link Prediction under the Structural Features of Attention Stream Network 注意流网络结构特征下的链接预测研究

2021 IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers (IPEC) Pub Date : 2021-04-14 DOI: 10.1109/IPEC51340.2021.9421305

Yong Li, Xinkai Liu, Changqing Wang

{"title":"Research on Link Prediction under the Structural Features of Attention Stream Network","authors":"Yong Li, Xinkai Liu, Changqing Wang","doi":"10.1109/IPEC51340.2021.9421305","DOIUrl":"https://doi.org/10.1109/IPEC51340.2021.9421305","url":null,"abstract":"The attention flow network is an important branch of network science, and the research on the link prediction algorithm of attention flow network has important theoretical and application value. The traditional link prediction algorithm based on the neighbor hypothesis cannot learn the global structure information of the network, while the traditional graph neural network algorithm needs to combine external information and has a large amount of calculation. Based on the structural characteristics and the advantages of the MLP neural network, this paper proposes a stru2vec-based algorithm. The link prediction SMLP algorithm is compared with the existing DeepWalk, Line, Node2vec, Hope, NetMF and other algorithms. It is found that the SMLP algorithm proposed in this paper improves on the four evaluation indicators of Precision, Recall, Accuracy and F1 by about 15.8% on average. The average increase in AUC index is about 12.1%, and the performance is better on the ROC curve, and the algorithm proposed in this paper focuses on learning the network structure, and has a good learning effect for the network with missing node label information and sparse self-characteristic attributes.","PeriodicalId":340882,"journal":{"name":"2021 IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers (IPEC)","volume":"128 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134243652","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 Photovoltaic Power Generation Based on Multi-Channel PID 基于多通道PID的光伏发电研究

2021 IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers (IPEC) Pub Date : 2021-04-14 DOI: 10.1109/IPEC51340.2021.9421313

Juan Liu, Xusheng Hu, Rui Zheng

引用次数: 0