发布求助
文献互助 智能选刊 最新文献

2022 IEEE 2nd International Conference on Power, Electronics and Computer Applications (ICPECA)最新文献

筛选
英文 中文
Innovation method optimization of digital platform enabler based on correlation analysis and gray prediction 基于关联分析和灰色预测的数字平台推动者创新方法优化
2022 IEEE 2nd International Conference on Power, Electronics and Computer Applications (ICPECA) Pub Date : 2022-01-21 DOI: 10.1109/ICPECA53709.2022.9718823
Z. Yiyu
{"title":"Innovation method optimization of digital platform enabler based on correlation analysis and gray prediction","authors":"Z. Yiyu","doi":"10.1109/ICPECA53709.2022.9718823","DOIUrl":"https://doi.org/10.1109/ICPECA53709.2022.9718823","url":null,"abstract":"Starting from the perspective of architecture design, this paper takes Alibaba Cloud IoT platform, Haier U+ platform and Huawei OceanConnect platform as case studies, and uses correlation analysis and gray prediction methods to explore how digital platforms can effectively empower complementary users to achieve digital innovation. It is found that modularity, stratification and platform boundary resource dynamics are the key dimensions of digital platform architecture design, and the key dimensions of digital platform architecture design are extracted to reveal the enabling mechanism of digital platform architecture design for complementarity innovation, which can provide a new idea for digital platform enabling complementarity innovation based on architecture design.","PeriodicalId":244448,"journal":{"name":"2022 IEEE 2nd International Conference on Power, Electronics and Computer Applications (ICPECA)","volume":"1427 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132215060","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
Evaluation Algorithm of Construction Project Safety Management Based on BP Neural Network 基于BP神经网络的建设项目安全管理评价算法
2022 IEEE 2nd International Conference on Power, Electronics and Computer Applications (ICPECA) Pub Date : 2022-01-21 DOI: 10.1109/ICPECA53709.2022.9719089
Jihuan Zhuo, Meiping Wang, Yuhao Wan, Xiudai Wang
{"title":"Evaluation Algorithm of Construction Project Safety Management Based on BP Neural Network","authors":"Jihuan Zhuo, Meiping Wang, Yuhao Wan, Xiudai Wang","doi":"10.1109/ICPECA53709.2022.9719089","DOIUrl":"https://doi.org/10.1109/ICPECA53709.2022.9719089","url":null,"abstract":"At present, China’s construction market has achieved competitive bidding at home and abroad, and more and more construction projects are determined by bidding. Although the development and application of new building technologies have solved many technical difficulties in engineering construction, construction projects are not only characterized by complex construction technologies, but also by large investment funds, long construction period, many participants and complex construction environment factors. The construction industry is also prone to safety accidents, which is one of the characteristics of the construction industry. Especially under the condition of non-standard and unscientific construction accident control and management, the annual losses caused by construction accidents are very huge, which also restricts the development process of China’s construction industry. This paper uses the bid evaluation model of BP neural network algorithm to evaluate the safety management of construction project.","PeriodicalId":244448,"journal":{"name":"2022 IEEE 2nd International Conference on Power, Electronics and Computer Applications (ICPECA)","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132359201","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
AICF: Attentional Item-interaction Collaborative Filtering 注意项目交互协同过滤
2022 IEEE 2nd International Conference on Power, Electronics and Computer Applications (ICPECA) Pub Date : 2022-01-21 DOI: 10.1109/ICPECA53709.2022.9719163
Tengyu Ma, Yuliang Shi
{"title":"AICF: Attentional Item-interaction Collaborative Filtering","authors":"Tengyu Ma, Yuliang Shi","doi":"10.1109/ICPECA53709.2022.9719163","DOIUrl":"https://doi.org/10.1109/ICPECA53709.2022.9719163","url":null,"abstract":"As of today, deep learning technology has been widely utilized in the field of recommendation algorithms. Many work utilizes the multilayer perceptrons to simulate inner product operations in matrix factorization (MF) models. Hence, those works inherit a weakness of MF, namely the ineffectiveness of identifying between a small group of closely related items. The association of items, such as high-order relations between items, endows the recommendation system with valuable information on the user’s final choices. In accordance with the above facts, this paper proposes an Attentional Item-Interaction Collaborative Filtering model (AICF). It can distinguish which items in the user’s historical interaction items play a more important role in the user’s choice of items. To examine the performance of AICF, we designed multiple experiments on two real world data sets.","PeriodicalId":244448,"journal":{"name":"2022 IEEE 2nd International Conference on Power, Electronics and Computer Applications (ICPECA)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134568689","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
KNN Virtual Currency Price Prediction Model Based on Price Trend Characteristics 基于价格趋势特征的KNN虚拟货币价格预测模型
2022 IEEE 2nd International Conference on Power, Electronics and Computer Applications (ICPECA) Pub Date : 2022-01-21 DOI: 10.1109/ICPECA53709.2022.9719057
Wei-chi Huang
{"title":"KNN Virtual Currency Price Prediction Model Based on Price Trend Characteristics","authors":"Wei-chi Huang","doi":"10.1109/ICPECA53709.2022.9719057","DOIUrl":"https://doi.org/10.1109/ICPECA53709.2022.9719057","url":null,"abstract":"Bitcoin presents a new monetary concept and has received a lot of interest from various parties, which in turn has created a new form of investment in virtual currencies. The prices of virtual currencies tend to change quickly and fluctuate greatly, causing many investors to rush into the market in a frenzy, ignoring the riskiness behind it. The price prediction of virtual currencies can not only provide reference for investors’ investment, but also reveal its financial laws to a certain extent, improve the risk warning mechanism, and enhance its stability and safety. In this paper, we propose an improved KNN algorithm for virtual currency price prediction. The new model restructures the data and converts the original single-point price data into the trend characteristics of the price. The experimental results show that the improved KNN model has better prediction effect compared with the traditional KNN model as well as the logistic regression model.","PeriodicalId":244448,"journal":{"name":"2022 IEEE 2nd International Conference on Power, Electronics and Computer Applications (ICPECA)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131489702","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
The Following System of 3D Simulation Manipulator 以下是三维仿真机械手系统
2022 IEEE 2nd International Conference on Power, Electronics and Computer Applications (ICPECA) Pub Date : 2022-01-21 DOI: 10.1109/ICPECA53709.2022.9719311
Jiawei Chen, Limin Mao, Zhiwen Song, M. Wang
{"title":"The Following System of 3D Simulation Manipulator","authors":"Jiawei Chen, Limin Mao, Zhiwen Song, M. Wang","doi":"10.1109/ICPECA53709.2022.9719311","DOIUrl":"https://doi.org/10.1109/ICPECA53709.2022.9719311","url":null,"abstract":"In this paper, the three-dimensional motion camera of Kinect sensor is used to scan the space where the human body is to capture human movements in real time, and in the upper machine processing platform real-time display of the human body movement state, analyze the action instructions corresponding to different actions of the human body, and complete the 3D simulation manipulator following the actions of the human body. After debugging, the system designed in this paper can accurately recognize gestures without obvious delay, and the manipulator can follow the human arm well.","PeriodicalId":244448,"journal":{"name":"2022 IEEE 2nd International Conference on Power, Electronics and Computer Applications (ICPECA)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131742367","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 Internet of Things and Traceability Technology in the Whole Industrial Chain in Mountainous Areas by Blockchain 区块链在山区全产业链物联网及可追溯技术的应用
2022 IEEE 2nd International Conference on Power, Electronics and Computer Applications (ICPECA) Pub Date : 2022-01-21 DOI: 10.1109/ICPECA53709.2022.9718882
Xiaojun Cui, Zihang Gao
{"title":"Application of Internet of Things and Traceability Technology in the Whole Industrial Chain in Mountainous Areas by Blockchain","authors":"Xiaojun Cui, Zihang Gao","doi":"10.1109/ICPECA53709.2022.9718882","DOIUrl":"https://doi.org/10.1109/ICPECA53709.2022.9718882","url":null,"abstract":"This paper through investigation and research on the whole process of the supply chain of bayberry in mountainous areas. Based on the advanced technology of information science such as blockchain and big data, we have created a complete set of traceability and supervision mechanisms such as the bayberry quality and safety of risk assessment and warning, all round supervision during the entire process, and crisis handling after the incident. In the process, by maintaining public health, ensuring the quality of agricultural products, and promoting industrial development, we have achieved an overall improvement in the living standards of farmers.","PeriodicalId":244448,"journal":{"name":"2022 IEEE 2nd International Conference on Power, Electronics and Computer Applications (ICPECA)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131753481","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 Intelligent Course Management System Based on Information Digitization and Database 基于信息数字化和数据库的智能课程管理系统研究
2022 IEEE 2nd International Conference on Power, Electronics and Computer Applications (ICPECA) Pub Date : 2022-01-21 DOI: 10.1109/ICPECA53709.2022.9719218
Qian Shao
{"title":"Research on Intelligent Course Management System Based on Information Digitization and Database","authors":"Qian Shao","doi":"10.1109/ICPECA53709.2022.9719218","DOIUrl":"https://doi.org/10.1109/ICPECA53709.2022.9719218","url":null,"abstract":"This system uses software engineering ideas as a whole, uses My Eclipse as a development environment, Java EE as a development standard, integrates Struts, Hibernate, and MVC to design the architecture and various modules, and uses MySQL database as the basis for the system modules Management of various types of data. This technology not only guarantees the performance of the system, but also covers the scope of general teaching management work. By dividing user roles and realizing hierarchical management, the work of teaching administrators at all levels is fast, convenient, accurate, and safe, and it also provides a good Resource sharing platform.","PeriodicalId":244448,"journal":{"name":"2022 IEEE 2nd International Conference on Power, Electronics and Computer Applications (ICPECA)","volume":"109 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132816117","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
Exploration and Analysis of the Path Optimization of Labour Recommendation Model Based on Big Data and Auto-Kg Algorithm 基于大数据和Auto-Kg算法的劳动力推荐模型路径优化探索与分析
2022 IEEE 2nd International Conference on Power, Electronics and Computer Applications (ICPECA) Pub Date : 2022-01-21 DOI: 10.1109/ICPECA53709.2022.9719269
Guisheng Hu
{"title":"Exploration and Analysis of the Path Optimization of Labour Recommendation Model Based on Big Data and Auto-Kg Algorithm","authors":"Guisheng Hu","doi":"10.1109/ICPECA53709.2022.9719269","DOIUrl":"https://doi.org/10.1109/ICPECA53709.2022.9719269","url":null,"abstract":"At present, labour education has a significant status and role in higher education. It not only meets the basic needs of students' social life, but it is also a measure of the comprehensive quality of students. Based on the perspective of big data and system dynamics, the article designs an adaptive college labour education learning system. The system includes domain model, learner model, adaptive model and cognitive diagnosis model. The article uses Auto-kg algorithm to construct a knowledge map of the learning content of labour education in colleges and universities. Design adaptive learning content recommendation strategy based on learner's learning style and realize adaptive recommendation of learning content. The results show that the recommendation model can significantly improve the learning effect of learners.","PeriodicalId":244448,"journal":{"name":"2022 IEEE 2nd International Conference on Power, Electronics and Computer Applications (ICPECA)","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133676184","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
Text classification of COVID-19 reviews based on pre-training language model 基于预训练语言模型的COVID-19综述文本分类
2022 IEEE 2nd International Conference on Power, Electronics and Computer Applications (ICPECA) Pub Date : 2022-01-21 DOI: 10.1109/ICPECA53709.2022.9719020
Juxing Di, Zixu Liu, Yang Yang
{"title":"Text classification of COVID-19 reviews based on pre-training language model","authors":"Juxing Di, Zixu Liu, Yang Yang","doi":"10.1109/ICPECA53709.2022.9719020","DOIUrl":"https://doi.org/10.1109/ICPECA53709.2022.9719020","url":null,"abstract":"This experiment analyzed 100,000 epidemic-related microblogs officially provided by the CCF. Using Enhanced Representation through Knowledge Integration (ERNIE), the effect of pre-training model on extracting Chinese semantic information was improved. After that, the deep pyramid network (DPCNN) was merged with ERNIE to save computing costs. Enhanced feature extraction performance for long-distance text. This model was the most effective in the comparison test of six emotional three-category tasks, which improved the accuracy of BERT pre-training model by 7%.","PeriodicalId":244448,"journal":{"name":"2022 IEEE 2nd International Conference on Power, Electronics and Computer Applications (ICPECA)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117291406","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 Optimizer Algorithm of Sign Language Recognition Model 手语识别模型优化算法研究
2022 IEEE 2nd International Conference on Power, Electronics and Computer Applications (ICPECA) Pub Date : 2022-01-21 DOI: 10.1109/ICPECA53709.2022.9719010
Yang-Jing Zhou, Chongxing Ji, Lijuan Cao
{"title":"Research on Optimizer Algorithm of Sign Language Recognition Model","authors":"Yang-Jing Zhou, Chongxing Ji, Lijuan Cao","doi":"10.1109/ICPECA53709.2022.9719010","DOIUrl":"https://doi.org/10.1109/ICPECA53709.2022.9719010","url":null,"abstract":"One of the most well-known tools for sign language recognition is neural network. There are many optimizer algorithms to improve the performance of the network. But previous studies of optimizer algorithms have not dealt with its convergence stability for sign language recognition. Therefore, we propose an optimizer algorithm for sign language recognition model, which has a good optimization effect on sign language recognition model based on LSTM neural network. We designed a sign language recognition model based on LSTM neural network, and carried out the experiment in the open dataset of SLR of University of science and technology of China. In the experiment, we added the classical optimizer algorithm for comparison. The experimental results show that. This paper proposes that the optimizer algorithm has better convergence stability than the classical algorithm, and has good adaptability to different input data.","PeriodicalId":244448,"journal":{"name":"2022 IEEE 2nd International Conference on Power, Electronics and Computer Applications (ICPECA)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117294984","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
首页 上一页 下一页 尾页
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整，为了账户安全，请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们：info@booksci.cn Book学术提供免费学术资源搜索服务，方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号：481959085
Book学术官方微信