2023 3rd International Conference on Consumer Electronics and Computer Engineering (ICCECE)最新文献

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Composition analysis and identification of ancient glass objects based on neural network models 基于神经网络模型的古代玻璃制品成分分析与鉴定
2023 3rd International Conference on Consumer Electronics and Computer Engineering (ICCECE) Pub Date : 2023-01-06 DOI: 10.1109/ICCECE58074.2023.10135338
Jianing Li, Yunfei Zhu
{"title":"Composition analysis and identification of ancient glass objects based on neural network models","authors":"Jianing Li, Yunfei Zhu","doi":"10.1109/ICCECE58074.2023.10135338","DOIUrl":"https://doi.org/10.1109/ICCECE58074.2023.10135338","url":null,"abstract":"This paper presents a model based on a 3-layer feedforward neural network, which effectively preserves the characteristics of the chemical content of each category in ancient glass through 3 fully connected layers. The average prediction rate of the model was 96.43%, which was 2.43% higher than the traditional KNN classification model, 3.42% higher than the support vector machine (SVM) model and 8.43% higher than the random forest model, demonstrating the efficiency of the model.","PeriodicalId":120030,"journal":{"name":"2023 3rd International Conference on Consumer Electronics and Computer Engineering (ICCECE)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114985914","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
An improved Harris Hawk optimization algorithm and its application to Extreme Learning Machine 一种改进的Harris Hawk优化算法及其在极限学习机中的应用
2023 3rd International Conference on Consumer Electronics and Computer Engineering (ICCECE) Pub Date : 2023-01-06 DOI: 10.1109/ICCECE58074.2023.10135354
Ziliang Liu, Hongwe Chen
{"title":"An improved Harris Hawk optimization algorithm and its application to Extreme Learning Machine","authors":"Ziliang Liu, Hongwe Chen","doi":"10.1109/ICCECE58074.2023.10135354","DOIUrl":"https://doi.org/10.1109/ICCECE58074.2023.10135354","url":null,"abstract":"The Harris Hawk optimization (HHO) algorithm is an excellent swarm intelligence optimization algorithm which has the advantages of high efficiency in finding the best, ease of implementation and wide application. It also has some disadvantages such as the possibility of convergence too fast and the tendency to fall into local optima. This paper combines an improved escape energy update approach and the leader update operator of the Salp Swarm Algorithm to improve the HHO, named IMHHO. The experiments show that the improvements have improved the algorithm's ability to find the best. IMHHO was also used in the parameter optimization of the Extreme Learning Machine, which also enables the ELM to find the right weights and bias values and to regress the data more accurately.","PeriodicalId":120030,"journal":{"name":"2023 3rd International Conference on Consumer Electronics and Computer Engineering (ICCECE)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115533040","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
Aircraft Trajectory Prediction Model Based on Improved GRU Structure 基于改进GRU结构的飞机轨迹预测模型
2023 3rd International Conference on Consumer Electronics and Computer Engineering (ICCECE) Pub Date : 2023-01-06 DOI: 10.1109/ICCECE58074.2023.10135263
Zexuan Chen, Lan Wang
{"title":"Aircraft Trajectory Prediction Model Based on Improved GRU Structure","authors":"Zexuan Chen, Lan Wang","doi":"10.1109/ICCECE58074.2023.10135263","DOIUrl":"https://doi.org/10.1109/ICCECE58074.2023.10135263","url":null,"abstract":"In view of the actual need to predict aircraft trajectory, traditional prediction models often have problems such as insufficient precision and slow training efficiency. By analyzing the target trajectory with temporal characteristics, the Elastic-BiGRU trajectory prediction model is proposed, which combines the Smooth filtering method, the Elastic Network fitting method and the GRU structure, the prediction accuracy of aircraft trajectory is further improved. The experimental results show that the Elastic-BiGRU model compared with Bi-LSTM model and Bi-GRU model, its MSE error is relatively reduced by more than 8% and 11%The Elastic-BiGRU also solves the problem of slow training speed of Bi-LSTM model, and saves about 20% of the time.","PeriodicalId":120030,"journal":{"name":"2023 3rd International Conference on Consumer Electronics and Computer Engineering (ICCECE)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115922987","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
Grouping Beamlet Transform for Surface Crack Detection 基于分组波束变换的表面裂纹检测
2023 3rd International Conference on Consumer Electronics and Computer Engineering (ICCECE) Pub Date : 2023-01-06 DOI: 10.1109/ICCECE58074.2023.10135447
Tian Cai, Weiwei Zhao, Zhe Lin, Pengfei Guo
{"title":"Grouping Beamlet Transform for Surface Crack Detection","authors":"Tian Cai, Weiwei Zhao, Zhe Lin, Pengfei Guo","doi":"10.1109/ICCECE58074.2023.10135447","DOIUrl":"https://doi.org/10.1109/ICCECE58074.2023.10135447","url":null,"abstract":"Beamlet transform is an excellent multiscale geometric analysis method. It has a great capacity of extracting line features from images under noise. However, it is too slow since a mass of redundant beamlets waste much time. In fact, only several of them are helpful in many applications. In this paper, grouping beamlet transform is presented to fasten line feature detection for surface crack detection. Geometric flows used in grouplet transform are introduced to determine geometric structures of an image. In each recursively partitioned box, only the beamlets along with major direction are generated. So that lots of useless beamlets for the image can be excluded from the following integral computation. Experiments on various optical images show that grouping beamlet transform is able to detect line features in an image the same as classic beamlet transform, however, the former runs much faster than the latter on any of the tested images. In some cases, only about 60% of consuming time in classic beamlet transform may be needed in grouping beamlet transform. As an improvement of beamlet transform, grouping beamlet transform will be more applicable in the field of surface crack detection.","PeriodicalId":120030,"journal":{"name":"2023 3rd International Conference on Consumer Electronics and Computer Engineering (ICCECE)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123742626","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
Design And Implementation Of Domestic High Reliability Measurement And Control Computer System 国产高可靠性测控计算机系统的设计与实现
2023 3rd International Conference on Consumer Electronics and Computer Engineering (ICCECE) Pub Date : 2023-01-06 DOI: 10.1109/ICCECE58074.2023.10135310
Jian Xiao, Junwei Wan, Hongyan Chen, Hongwei Qi, Zhifang Yao, Li Zhang
{"title":"Design And Implementation Of Domestic High Reliability Measurement And Control Computer System","authors":"Jian Xiao, Junwei Wan, Hongyan Chen, Hongwei Qi, Zhifang Yao, Li Zhang","doi":"10.1109/ICCECE58074.2023.10135310","DOIUrl":"https://doi.org/10.1109/ICCECE58074.2023.10135310","url":null,"abstract":"At present, the number of users and data capacity of space TT&C missions are increasing, which puts forward higher requirements for the reliability of computer systems and autonomous and controllable security. Aiming at the information processing application and command management needs of space missions under the new situation, the architecture design of aerospace measurement and control computer system with domestic hardware and independent controllable basic software as the core is proposed. It solves the problems of dual-route customized transmission, dual-network multicast sharding coverage of the same channel, secure sharing of real-time files, accurate synchronization of homologous multiple signals in the high-stream video lossless compression display control system under IP network, and multi-source signal fusion, etc. The design and integrated implementation of this computer system plays a major role in the field of manned spaceflight measurement and control, satellite launch technology for high real-time, high reliability, high scalability and high security of the central business system.","PeriodicalId":120030,"journal":{"name":"2023 3rd International Conference on Consumer Electronics and Computer Engineering (ICCECE)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122585611","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 Control Technology of Mine High Energy density permanent magnet Direct Drive Integrated Machine based on fuzzy PID 基于模糊PID的矿用高能量密度永磁直驱一体机控制技术研究
2023 3rd International Conference on Consumer Electronics and Computer Engineering (ICCECE) Pub Date : 2023-01-06 DOI: 10.1109/ICCECE58074.2023.10135343
Sen Wang, Nan Chen, Yunpeng Deng, Daili Liang, Yanhui Xiao, Wenshuo Wang, W. Yu, Lei Wang, Yuqin Zhu, Li Zhang, Hao Liu, Zhanyang Yu, Jianmin Du
{"title":"Research on Control Technology of Mine High Energy density permanent magnet Direct Drive Integrated Machine based on fuzzy PID","authors":"Sen Wang, Nan Chen, Yunpeng Deng, Daili Liang, Yanhui Xiao, Wenshuo Wang, W. Yu, Lei Wang, Yuqin Zhu, Li Zhang, Hao Liu, Zhanyang Yu, Jianmin Du","doi":"10.1109/ICCECE58074.2023.10135343","DOIUrl":"https://doi.org/10.1109/ICCECE58074.2023.10135343","url":null,"abstract":"In order to improve the mining high energy density of permanent magnet direct drive all-in-one control performance and anti-interference ability, for the traditional PID control performance efficiency is not high, and the working environment changes, through the traditional PID control and fuzzy PID control control performance, puts forward a smart control method based on fuzzy PID control. The simulation model of the fuzzy PID controller is constructed and the simulation experiment is conducted. The simulation results show that the fuzzy PID controller, compared with the traditional PID controller, has stronger reliability.","PeriodicalId":120030,"journal":{"name":"2023 3rd International Conference on Consumer Electronics and Computer Engineering (ICCECE)","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122644166","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
Transmission Line Fault Diagnosis Based on Machine Learning 基于机器学习的输电线路故障诊断
2023 3rd International Conference on Consumer Electronics and Computer Engineering (ICCECE) Pub Date : 2023-01-06 DOI: 10.1109/ICCECE58074.2023.10135452
Fuqing Hao, Xiaoting Yang, Guoqiang Wang, Yeji Feng
{"title":"Transmission Line Fault Diagnosis Based on Machine Learning","authors":"Fuqing Hao, Xiaoting Yang, Guoqiang Wang, Yeji Feng","doi":"10.1109/ICCECE58074.2023.10135452","DOIUrl":"https://doi.org/10.1109/ICCECE58074.2023.10135452","url":null,"abstract":"In this paper, a faulted phase selection scheme for extracting MPE values of fault transient voltage signals and combining them with CS-SVM for high-voltage transmission lines is proposed. The results show that using MPE to quantify the transient voltage signal in high-voltage transmission lines can fully reflect the fault transient signal characteristics, can be accurately judged within a small time window, identifies faults with high accuracy, is not affected by the fault occurrence location, transition resistance size, and the initial angle state of fault occurrence, and can overcome the defect that the voltage signal has weak sensitivity at the strong power side of the system.","PeriodicalId":120030,"journal":{"name":"2023 3rd International Conference on Consumer Electronics and Computer Engineering (ICCECE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130181228","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 Key Technologies of 5G Radio Access Network(RAN) for Nuclear Power Plant Industry Applications 核电厂工业应用5G无线接入网关键技术研究
2023 3rd International Conference on Consumer Electronics and Computer Engineering (ICCECE) Pub Date : 2023-01-06 DOI: 10.1109/ICCECE58074.2023.10135392
Qiaoman Duan, Yangyang Cao, Yinwei Wu, Haopeng Zhang, Songtao Gao, Xiangchen Ma
{"title":"Research on Key Technologies of 5G Radio Access Network(RAN) for Nuclear Power Plant Industry Applications","authors":"Qiaoman Duan, Yangyang Cao, Yinwei Wu, Haopeng Zhang, Songtao Gao, Xiangchen Ma","doi":"10.1109/ICCECE58074.2023.10135392","DOIUrl":"https://doi.org/10.1109/ICCECE58074.2023.10135392","url":null,"abstract":"With the gradual maturity of 5G network development and the continuous enrichment of application scenarios, 5G has become an important supporting technology in the process of network and intelligent transformation of traditional industries. Under the background of the rapid development of information communication demand in the nuclear power plant industry, this paper analyzes the business requirements of the current nuclear power plant wireless communication scenarios, clarifies that 5G is the main solution to the nuclear power plant wireless communication demand, and further studies the 5G radio access network (RAN) construction mode. According to the characteristics and difficulties of communication requirements in nuclear power plants, the key technologies of 5G RAN in nuclear power plants are studied.","PeriodicalId":120030,"journal":{"name":"2023 3rd International Conference on Consumer Electronics and Computer Engineering (ICCECE)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130295414","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 Power Load Forecasting Based on Deep Learning 基于深度学习的电力负荷预测研究
2023 3rd International Conference on Consumer Electronics and Computer Engineering (ICCECE) Pub Date : 2023-01-06 DOI: 10.1109/ICCECE58074.2023.10135242
Lanxin Lin, Jingxin Yao, Kun Wang
{"title":"Research on Power Load Forecasting Based on Deep Learning","authors":"Lanxin Lin, Jingxin Yao, Kun Wang","doi":"10.1109/ICCECE58074.2023.10135242","DOIUrl":"https://doi.org/10.1109/ICCECE58074.2023.10135242","url":null,"abstract":"In order to fully explore the time-series correlation of power load data and improve the prediction accuracy of power load, this paper proposes a neural network-based deep learning approach for power load prediction. Firstly, the relevant electric power data are obtained and divided into appropriate sample sizes, and the samples are normalized; then, a prediction model based on LSTM is built to explore the correlation between different features, and the corresponding model of this neural network is further trained and validated on the data test set; finally, a comparison between LSTM and other algorithms such as SVM, ANN, GAOS and GM are performed. The results show that the LSTM prediction algorithm can better track the trend of power load change, with higher prediction accuracy and efficiency.","PeriodicalId":120030,"journal":{"name":"2023 3rd International Conference on Consumer Electronics and Computer Engineering (ICCECE)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130340773","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
Study on active distribution network dispatch strategy based on dynamic partition optimization 基于动态分区优化的配电网主动调度策略研究
2023 3rd International Conference on Consumer Electronics and Computer Engineering (ICCECE) Pub Date : 2023-01-06 DOI: 10.1109/ICCECE58074.2023.10135264
Yunmin Wang, Wenyi Li, Ziwen Liang
{"title":"Study on active distribution network dispatch strategy based on dynamic partition optimization","authors":"Yunmin Wang, Wenyi Li, Ziwen Liang","doi":"10.1109/ICCECE58074.2023.10135264","DOIUrl":"https://doi.org/10.1109/ICCECE58074.2023.10135264","url":null,"abstract":"The goal of active distribution network (ADN) is to improve the capacity of the existing distribution network for intermittent renewable energy (IRE) generation on the premise of ensuring the reliability of grid operation and power quality. In order to promote the consumption of IRE in ADN,this paper establishes an optimization dispatch strategy of active distribution network with energy storage system and controllable load participating in the regulation.An optimization dispatch strategy-dynamic partition is proposed, and an advanced artificial fish swarm algorithm is proposed to enhance the local searching ability. Finally,the effectiveness of the proposed strategy is verified by the case on an improved IEEE 33 node system.","PeriodicalId":120030,"journal":{"name":"2023 3rd International Conference on Consumer Electronics and Computer Engineering (ICCECE)","volume":"39 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130982764","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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