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Power line recognition method based on Hough and YOLO fusion 基于Hough和YOLO融合的电力线识别方法
International Conference on Electronic Information Technology Pub Date : 2023-08-15 DOI: 10.1117/12.2685471
Yu Gong, Xiaohong Liu
{"title":"Power line recognition method based on Hough and YOLO fusion","authors":"Yu Gong, Xiaohong Liu","doi":"10.1117/12.2685471","DOIUrl":"https://doi.org/10.1117/12.2685471","url":null,"abstract":"Aiming at the problem of power line target recognition in the process of power patrol inspection, this paper proposes a power line detection method that combines Hough and YOLO, as common detection algorithms often cannot accurately identify and determine the location of targets such as power lines and towers. Acquire image edge features through edge detection, and extract line features in the image using Houhg detection. After determining the line features to be selected, use the YOLO algorithm as a convolutional neural network framework to identify power lines and tower targets based on the migration learning process. Fusion of the target identification frame and the selected line is performed, mainly through rules such as intersection and slope judgment processes to eliminate interfering line segments, Finally, determine the exact location of the power line. After testing, the fusion method can well solve the problem of image line detection and location determination.","PeriodicalId":305812,"journal":{"name":"International Conference on Electronic Information Technology","volume":"12719 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130761345","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
Application of neural network algorithm in electromechanical automatic control system 神经网络算法在机电自动控制系统中的应用
International Conference on Electronic Information Technology Pub Date : 2023-08-15 DOI: 10.1117/12.2685848
Shuangdong Ya
{"title":"Application of neural network algorithm in electromechanical automatic control system","authors":"Shuangdong Ya","doi":"10.1117/12.2685848","DOIUrl":"https://doi.org/10.1117/12.2685848","url":null,"abstract":"In order to understand the application effect of electromechanical automatic control system, a neural network algorithm in the application of electromechanical automatic control system is proposed. This paper firstly analyzes the concept of electrical automation and neural network algorithm in detail, and then describes the advantages of neural network algorithm in electrical automatic control. Finally, the application of neural network algorithm in electrical automatic control is analyzed. In this paper, the application of neural network algorithm in electrical engineering automation is analyzed, and some suggestions are provided for the development of electrical engineering automation.","PeriodicalId":305812,"journal":{"name":"International Conference on Electronic Information Technology","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132777969","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 and application of 10kV cable condition assessment online monitoring device based on improved fuzzy theory 基于改进模糊理论的10kV电缆状态评估在线监测装置的研究与应用
International Conference on Electronic Information Technology Pub Date : 2023-08-15 DOI: 10.1117/12.2685890
Zong Jin, Jiakui Yang, Zihan Zhang, J. Zang
{"title":"Research and application of 10kV cable condition assessment online monitoring device based on improved fuzzy theory","authors":"Zong Jin, Jiakui Yang, Zihan Zhang, J. Zang","doi":"10.1117/12.2685890","DOIUrl":"https://doi.org/10.1117/12.2685890","url":null,"abstract":"Distribution cable is an important part of distribution network, and its running state has an important influence on the normal operation of distribution network. At present, the maintenance of distribution cables is mainly based on offline regular maintenance mechanism, which cannot monitor the operation status of cables in real time, and the regular maintenance is not targeted and the monitoring method is relatively single. Therefore, the comprehensive evaluation method of improved fuzzy theory is used to evaluate the operation state of distribution cable, and a set of cable on-line monitoring device is designed. The designed device is installed and debugged on site, which verifies that the device can effectively monitor the state of cable.","PeriodicalId":305812,"journal":{"name":"International Conference on Electronic Information Technology","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131677887","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
Offloading strategy for dependency-aware tasks in MEC system based on deep Q-network 基于深度q网络的MEC系统中依赖感知任务的卸载策略
International Conference on Electronic Information Technology Pub Date : 2023-08-15 DOI: 10.1117/12.2685767
Rui Yuan, Wei Jiang, Jing Hu, Tiecheng Song
{"title":"Offloading strategy for dependency-aware tasks in MEC system based on deep Q-network","authors":"Rui Yuan, Wei Jiang, Jing Hu, Tiecheng Song","doi":"10.1117/12.2685767","DOIUrl":"https://doi.org/10.1117/12.2685767","url":null,"abstract":"Task offloading strategy is one of the promising methods in mobile edge computing (MEC) to reschedule computing resources. Scheduling for computationally intensive tasks was mainly focused on and the dependency restriction between tasks was generally ignored. In this paper, an End-to-Edge collaborative resource allocation model is established. Firstly, in order to improve the unrealistic assumption raised in previous studies that tasks can be offloaded to MEC servers with arbitrary proportion and order, we establish the directed acyclic graphs to describe the dependency relationship within tasks. And then, system time cost including execution time, transmission delay and waiting latency are considered, and the task offloading problem is transformed into an optimization model to minimize time consumption. To manage the non-convex problem, an offloading strategy under dependency constraints based on deep Q-network (DQN) is proposed. Simulations prove that the proposed algorithm can obtain smaller time cost by comparing with other baseline algorithms.","PeriodicalId":305812,"journal":{"name":"International Conference on Electronic Information Technology","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125464730","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 and implementation of modularization of embedded software for data chains 数据链嵌入式软件模块化的研究与实现
International Conference on Electronic Information Technology Pub Date : 2023-08-15 DOI: 10.1117/12.2685676
Yikun Wu, Hai Luo, Yu Liu
{"title":"Research and implementation of modularization of embedded software for data chains","authors":"Yikun Wu, Hai Luo, Yu Liu","doi":"10.1117/12.2685676","DOIUrl":"https://doi.org/10.1117/12.2685676","url":null,"abstract":"The article researches and implements the embedded software of data chain from the perspective of modular development. Firstly, the current development trend of data chain technology and the pain points of software development are introduced. In contrast to the challenges faced by the traditional model, the architecture of modular software design is studied, the functions of each level are analyzed, and the design scheme and advantages are explained. Finally, the specific ideas and standard interfaces of modular software implementation are illustrated with code engineering, and the implementation steps and related results in the application process are introduced.","PeriodicalId":305812,"journal":{"name":"International Conference on Electronic Information Technology","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121203041","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
Wordle data mining based on deep learning 基于深度学习的世界数据挖掘
International Conference on Electronic Information Technology Pub Date : 2023-08-15 DOI: 10.1117/12.2685595
Jianjie Song, Fangyuan Zhu, Zirong Zhang
{"title":"Wordle data mining based on deep learning","authors":"Jianjie Song, Fangyuan Zhu, Zirong Zhang","doi":"10.1117/12.2685595","DOIUrl":"https://doi.org/10.1117/12.2685595","url":null,"abstract":"In just a few months, Wordle has grown from a few players to several million users after \"viral spread\" by major social platforms. To study the secret of Wordle game success We construct a time-series based model by building a QL-LSTM model to explain the daily variation in the number of reported results and try to predict the game reports on March 1, 2023, which has a prediction interval of [21127, 24093], while we construct features for vowel and consonant digits, wordiness, number of letter repetitions, and word frequency. and assessed the relevance and significance of the percentage of those reporting being in hard mode. Only word frequency and percentage in hard mode had a slightly negative and significant relationship. The mystery of Wordle is unveiled by the above exploration.","PeriodicalId":305812,"journal":{"name":"International Conference on Electronic Information Technology","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124909680","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
Method based on t-sne reduction and K-means clustering to identify the household-transformer relationship in low-voltage distribution network 基于t-sne约简和k均值聚类的低压配电网家用变压器关系识别方法
International Conference on Electronic Information Technology Pub Date : 2023-08-15 DOI: 10.1117/12.2685821
wenbin liu, Wenzheng Shao, Yang Xin
{"title":"Method based on t-sne reduction and K-means clustering to identify the household-transformer relationship in low-voltage distribution network","authors":"wenbin liu, Wenzheng Shao, Yang Xin","doi":"10.1117/12.2685821","DOIUrl":"https://doi.org/10.1117/12.2685821","url":null,"abstract":"Aiming at the current problems of low-voltage distribution network (LVDN) at present due to the untimely updating of the account in the early stage, which leads to the unclear relationship between customers and affects the operation, management and fault research and judgment of distribution network, this paper presents an automatic identification method of distribution network topology on the basis of clustering of historical voltage data and its fluctuation characteristics. Firstly, the three-phase voltage data and user terminal voltage of the adjacent substation in the research object station area are collected through the distribution intelligent terminal, and the multi-dimensional fluctuation characteristic parameters of the voltage at both ends are defined and calculated, and the global fluctuation characteristics and local fluctuation characteristics of the voltage series are mainly analyzed; Then, the dimension of the target data is then reduced using the t ⁃ sne algorithm; Finally, based on the characteristics of voltage fluctuation after dimensionality reduction, the correct relationship between substation transformers and users was obtained by using an improved K ⁃ means clustering algorithm for clustering substation transformers and users. The result of the example shows that the subordinate relationship between the user and the transformer in the topology of the target station area can be identified through the detailed analysis of the voltage measurement data at both ends of the target station area.","PeriodicalId":305812,"journal":{"name":"International Conference on Electronic Information Technology","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122406257","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
Automatic count of wheat ears in field wheat by improved YOLOv7 改良YOLOv7型大田小麦穗自动计数
International Conference on Electronic Information Technology Pub Date : 2023-08-15 DOI: 10.1117/12.2685526
Suyang Zhong, Tianle Wu, X. Geng, Zhenyi Li
{"title":"Automatic count of wheat ears in field wheat by improved YOLOv7","authors":"Suyang Zhong, Tianle Wu, X. Geng, Zhenyi Li","doi":"10.1117/12.2685526","DOIUrl":"https://doi.org/10.1117/12.2685526","url":null,"abstract":"Considering the difficulty of counting wheat sheaves in the field, this paper proposes an improved Yolov7 (YOU ONLY LOOKCE version 7) model for the automatic counting of wheat sheaves in the field. Based on Yolov7, the method adds a simple parameter-free attention module (SimAM) and full-dimensional dynamic convolution (ODConv), which can enhance the dimensional interactivity of the backbone network in extracting features. By introducing a centralised feature pyramid (CFP) into the neck structure, a comprehensive and differentiated feature representation can be effectively obtained. The improved Yolov7 model improves the applicability of automatic wheat counting and allows for better suppression of useless information in complex field environments. Several models were selected for comparative testing in the collected wheat head dataset, and the results showed that the improved Yolov7 achieved an average accuracy of 96.5%, outperforming other target detection models and allowing more accurate identification of wheat spike counts.","PeriodicalId":305812,"journal":{"name":"International Conference on Electronic Information Technology","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131508845","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
Multivariate time series prediction based on quantum enhanced LSTM models 基于量子增强LSTM模型的多变量时间序列预测
International Conference on Electronic Information Technology Pub Date : 2023-08-15 DOI: 10.1117/12.2685468
Dian-pu Li
{"title":"Multivariate time series prediction based on quantum enhanced LSTM models","authors":"Dian-pu Li","doi":"10.1117/12.2685468","DOIUrl":"https://doi.org/10.1117/12.2685468","url":null,"abstract":"Long short-term memory (LSTM) is a widely used artificial neural network that is well suited for time series prediction. Quantum machine learning as a new research topic combines the advantages of quantum data processing and classical machine learning. In this paper, based on a hybrid quantum classical scheme, we design a quantum enhanced LSTM model and several variants such as QGRU. We also performed experiments with a multivariate time series prediction problem to verify the feasibility of these models. Through this research, we expect to explore the benefits and implementation of quantum-based machine learning.","PeriodicalId":305812,"journal":{"name":"International Conference on Electronic Information Technology","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130195979","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
Handwritten digit recognition based on improved convolution neural network 基于改进卷积神经网络的手写数字识别
International Conference on Electronic Information Technology Pub Date : 2023-08-15 DOI: 10.1117/12.2685784
Liang Wang, Chunling Wang, Zi-ang Chen, Yang Qian
{"title":"Handwritten digit recognition based on improved convolution neural network","authors":"Liang Wang, Chunling Wang, Zi-ang Chen, Yang Qian","doi":"10.1117/12.2685784","DOIUrl":"https://doi.org/10.1117/12.2685784","url":null,"abstract":"An improved convolution neural network model is proposed, which has higher recognition rate for handwritten digits. Based on the AlexNet network model, the algorithm improves the feature extraction ability of the model by introducing residual module to modify the third and fourth volume layers in the model. The batch normalization (BN) method is used to prevent over-fitting after each convolution. In order to reduce the amount of computation, a full connection layer is reduced. The algorithm has a good effect on handwritten digit recognition by training and testing on MNIST dataset. Compared with AlexNet network model, the improved model has higher detection accuracy.","PeriodicalId":305812,"journal":{"name":"International Conference on Electronic Information Technology","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132776303","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
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