2021 IEEE International Conference on Electronic Technology, Communication and Information (ICETCI)最新文献_第3页

Scenic area data analysis based on NLP and ridge regression 基于NLP和岭回归的景区数据分析

2021 IEEE International Conference on Electronic Technology, Communication and Information (ICETCI) Pub Date : 2021-08-27 DOI: 10.1109/ICETCI53161.2021.9563582

Chen Liu

{"title":"Scenic area data analysis based on NLP and ridge regression","authors":"Chen Liu","doi":"10.1109/ICETCI53161.2021.9563582","DOIUrl":"https://doi.org/10.1109/ICETCI53161.2021.9563582","url":null,"abstract":"With the rapid development of Internet technology, many textual evaluation data of tourist destinations have accumulated on the Internet. Using NLP to conduct text mining on the data can effectively improve tourists' satisfaction and has a long-term and positive effect on the scientific supervision of tourism enterprises and the optimal allocation of resources. This paper uses Python to pre-process the comment data, including de-duplication, removal of English text, conversion of traditional Chinese to simplified, text correction, and compression to remove words. The reviews are divided into five categories: service, location, facility, hygiene, and cost-performance. The Paddlehub library is used to calculate the emotional scores of all reviews in the five aspects of each scenic spot and hotel and subsequently calculate the percentage of positive, neutral, and negative reviews. Afterward, use Ridge Regression and k-fold cross-validation to establish a comprehensive evaluation model, which can obtain the total score of each scenic spot and hotel in five aspects, with MSE, RMSE, MAE to verify. Furthermore, a method of extracting characteristic words in scenic spots and hotels is proposed: firstly, use the LDA subject vocabulary mining; next, select the TOP50 words through operations such as extracting keywords, selecting out nouns, filtering out irrelevant words, and synonymous merge; lastly, two parts of words are integrated to get the characteristic words. Finally, according to the total score, the scenic spots and hotels are divided into three levels: high, medium, and low levels, while three groups of scenic spots and hotels of the same type are selected respectively (each group has three scenic spots or hotels of different level). Through the characteristic words and five aspects of the total score, we can compare and analyze the selected three groups of scenic spots and hotels to make a suggestion.","PeriodicalId":170858,"journal":{"name":"2021 IEEE International Conference on Electronic Technology, Communication and Information (ICETCI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129589743","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

Flight Test Intelligent Mission Planning System Based on Big Data Platform 基于大数据平台的试飞智能任务规划系统

2021 IEEE International Conference on Electronic Technology, Communication and Information (ICETCI) Pub Date : 2021-08-27 DOI: 10.1109/ICETCI53161.2021.9563537

H. Zeyuan, Wang Huahui, Liu NanBo

引用次数: 0

Signals Recognition of Underwater Acoustic Communication based on Artificial Neural Network and Signal Feature Extraction 基于人工神经网络和信号特征提取的水声通信信号识别

2021 IEEE International Conference on Electronic Technology, Communication and Information (ICETCI) Pub Date : 2021-08-27 DOI: 10.1109/ICETCI53161.2021.9563404

Lei Kou, Xiaodong Gong, Yi Zheng, Xiuhui Ni, Xiangchao Feng, Fang Wang, Xinjuan Li, Quande Yuan, Ya-nan Dong

{"title":"Signals Recognition of Underwater Acoustic Communication based on Artificial Neural Network and Signal Feature Extraction","authors":"Lei Kou, Xiaodong Gong, Yi Zheng, Xiuhui Ni, Xiangchao Feng, Fang Wang, Xinjuan Li, Quande Yuan, Ya-nan Dong","doi":"10.1109/ICETCI53161.2021.9563404","DOIUrl":"https://doi.org/10.1109/ICETCI53161.2021.9563404","url":null,"abstract":"Modulation pattern recognition is an important part of underwater acoustic communication. Due to the complexity of underwater acoustic media (propagation loss, ocean noise, multipath effect and Doppler effect), underwater acoustic channel is considered to be one of the most challenging wireless communication channels. This paper proposed an intelligent underwater acoustic signal processing and recognition method based on artificial neural network (ANN) and signal feature extraction. Firstly, the real part and imaginary part of the signal are extracted by fast Fourier transform (FFT), the variance, mean and other eigenvalues of the real part and imaginary part are calculated, respectively. Secondly, the extracted signal features are used to train ANN classifier to realize the classification and recognition of different signals. In this way, the intelligent recognition of underwater acoustic signal by data-driven method is realized. Finally, the effectiveness of the proposed method is verified by simulation, and the good recognition effect is achieved.","PeriodicalId":170858,"journal":{"name":"2021 IEEE International Conference on Electronic Technology, Communication and Information (ICETCI)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127223709","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 of the Propagation Characteristic of Electromagnetic Wave in the Human Body 电磁波在人体中的传播特性研究

2021 IEEE International Conference on Electronic Technology, Communication and Information (ICETCI) Pub Date : 2021-08-27 DOI: 10.1109/ICETCI53161.2021.9563433

Mengxi Yang, Zhangfan Ye

引用次数: 0

Network security situation prediction based on optimized BP neural network 基于优化BP神经网络的网络安全态势预测

2021 IEEE International Conference on Electronic Technology, Communication and Information (ICETCI) Pub Date : 2021-08-27 DOI: 10.1109/ICETCI53161.2021.9563590

Yunfeng Zhang, Cheng He, Han Wu

{"title":"Network security situation prediction based on optimized BP neural network","authors":"Yunfeng Zhang, Cheng He, Han Wu","doi":"10.1109/ICETCI53161.2021.9563590","DOIUrl":"https://doi.org/10.1109/ICETCI53161.2021.9563590","url":null,"abstract":"With the rapid development of the network, the scale of the network has continued to expand, and network security issues have become increasingly prominent. Data from the National Internet Emergency Response Center show that my country's computer malicious programs, DDoS attacks, information security vulnerabilities, website implantation, and other threats have all been multiplied. The increasing trend. To respond to network security issues promptly and grasp the network security situation, predicting the network security situation has become important research in recent years. This paper proposes a network security situation prediction based on an optimized BP neural network. By analyzing the data, extracting the characteristics of security-related elements in the network, using the BP neural network to continuously adjust the weights and thresholds, the actual output value of the network is compared with the expected value. The error means the square error is the smallest, and the nonlinear mapping relationship of the network situation value is found. And through the simulated annealing algorithm (Simulated Annealing, SA) to optimize the BP neural network to avoid falling into the local minimum, to predict the network security situation. Simulation experiments verify the feasibility and effectiveness of the proposed method in network security situation prediction.","PeriodicalId":170858,"journal":{"name":"2021 IEEE International Conference on Electronic Technology, Communication and Information (ICETCI)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130838678","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

Optimization of User Feature Extraction Algorithm Comprehensive Innovation System for Students in the Era of Computer Internet Big Data 计算机互联网大数据时代学生用户特征提取算法综合创新体系优化

2021 IEEE International Conference on Electronic Technology, Communication and Information (ICETCI) Pub Date : 2021-08-27 DOI: 10.1109/ICETCI53161.2021.9563604

Peng Zang

{"title":"Optimization of User Feature Extraction Algorithm Comprehensive Innovation System for Students in the Era of Computer Internet Big Data","authors":"Peng Zang","doi":"10.1109/ICETCI53161.2021.9563604","DOIUrl":"https://doi.org/10.1109/ICETCI53161.2021.9563604","url":null,"abstract":"Ideological and political courses, as the main channel for cultivating students' world outlook, values, outlook on life and socialist core values, occupy an important position in the ideological and political education of colleges and universities. Aiming at the problems of traditional multimedia teaching methods, such as emphasizing skills and neglecting teaching, rigid use and lack of selectivity, this paper designs and implements an ideological and political teaching system based on big data analysis. The system consists of two parts: multimedia teaching software and computer big data recommendation. The multimedia teaching software realizes online teaching and resource management functions based on the B/S architecture. The big data recommendation subsystem recommends more suitable learning resources to users by collecting and analyzing user behaviors and extracting user characteristics. The function realization and performance test results show that the system has realized the teaching mode with students as the main body. It can not only effectively enhance the learning experience of students, but also support multiple people to learn online at the same time, which can effectively enhance students' learning initiative.","PeriodicalId":170858,"journal":{"name":"2021 IEEE International Conference on Electronic Technology, Communication and Information (ICETCI)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127884657","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

Polarity Search of Ternary FPRM Circuit Based on DMMA Algorithm 基于DMMA算法的三元FPRM电路极性搜索

2021 IEEE International Conference on Electronic Technology, Communication and Information (ICETCI) Pub Date : 2021-08-27 DOI: 10.1109/ICETCI53161.2021.9563531

Weichao Chen, Qiang Fu, Junwen Wei

引用次数: 0

Process Adaptability Research of Intelligent Upgrading for Traditional Container Terminals 传统集装箱码头智能化升级过程适应性研究

2021 IEEE International Conference on Electronic Technology, Communication and Information (ICETCI) Pub Date : 2021-08-27 DOI: 10.1109/ICETCI53161.2021.9563525

Luxu Huang, Jiahai Zhou

引用次数: 1

Study on the Chinese Vessel Crew Boom Index Model 中国船舶船员吊臂指数模型研究

2021 IEEE International Conference on Electronic Technology, Communication and Information (ICETCI) Pub Date : 2021-08-27 DOI: 10.1109/ICETCI53161.2021.9563506

Zilai Cheng, Yongmin Zhang

引用次数: 0

The application of meta-learning in the field of disease prediction and detection 元学习在疾病预测与检测领域的应用

2021 IEEE International Conference on Electronic Technology, Communication and Information (ICETCI) Pub Date : 2021-08-27 DOI: 10.1109/ICETCI53161.2021.9563551

Yujing Xia, Xiaoai Gu, Lin Liu, Lin Tang

引用次数: 0