2022 IEEE Conference on Telecommunications, Optics and Computer Science (TOCS)最新文献_第3页

Integrated Planning & Scheduling Model and Optimization Simulation of Multi-base Collaborative Manufacturing for Cement Industry 水泥工业多基地协同制造集成计划调度模型及优化仿真

2022 IEEE Conference on Telecommunications, Optics and Computer Science (TOCS) Pub Date : 2022-12-11 DOI: 10.1109/TOCS56154.2022.10016150

Xiaoxue Shang, Changchun Pan

引用次数: 0

Pivot-based Unsupervised Domain Adaptation for Pre-trained Language Model 基于轴向的预训练语言模型无监督域自适应

2022 IEEE Conference on Telecommunications, Optics and Computer Science (TOCS) Pub Date : 2022-12-11 DOI: 10.1109/TOCS56154.2022.10016201

Zhang Pengyu, Zhang Wenkang, Xing Zhiqiang

{"title":"Pivot-based Unsupervised Domain Adaptation for Pre-trained Language Model","authors":"Zhang Pengyu, Zhang Wenkang, Xing Zhiqiang","doi":"10.1109/TOCS56154.2022.10016201","DOIUrl":"https://doi.org/10.1109/TOCS56154.2022.10016201","url":null,"abstract":"In the task of text classification, natural language processing technology provides an effective solution for automatically identifying text content classification, but labeled data is difficult to obtain in specific domains. To reduce manual labeling, some researchers have proposed unsupervised domain adaptation technology, which is a special transfer learning technology, transferring source domain models suitable for general knowledge to the target domain with less labeled data, to improve the generalization effect of the model in the target domain. However, the current unsupervised domain adaptation methods are mostly to fine-tune the pre-trained model directly using unsupervised data from the target domain. This method needs a large amount of unsupervised data as usual to improve the training effect. Therefore, this paper presents a pivot-based unsupervised domain adaptation method, which extracts and masks pivots from unsupervised data, fine-tunes the pre-trained language model, and finally validates the method using supervised training, compared with the method of directly using unsupervised data to fine-tune the original model. The pivot-based domain adaptation method effectively improves the efficiency of domain knowledge transfer for the specific domain.","PeriodicalId":227449,"journal":{"name":"2022 IEEE Conference on Telecommunications, Optics and Computer Science (TOCS)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130164271","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

Trajectory Prediction Method of Millimeter-Wave Radar Based on Markov Model for Roadside Installation Scenario 基于马尔可夫模型的毫米波雷达道路安装场景轨迹预测方法

2022 IEEE Conference on Telecommunications, Optics and Computer Science (TOCS) Pub Date : 2022-12-11 DOI: 10.1109/TOCS56154.2022.10016148

Baidong Ma, Haiqing Liu, H. Fang

{"title":"Trajectory Prediction Method of Millimeter-Wave Radar Based on Markov Model for Roadside Installation Scenario","authors":"Baidong Ma, Haiqing Liu, H. Fang","doi":"10.1109/TOCS56154.2022.10016148","DOIUrl":"https://doi.org/10.1109/TOCS56154.2022.10016148","url":null,"abstract":"In the application of roadside traffic detection, when the wide-area millimeter-wave radar detects the target, due to the limits of target occlusion, detection angle and detection range, the problem of missing target trajectory points will be inevitable. Aiming at solving this problem, a target trajectory prediction method based on Markov is proposed. This method predicts the four characteristic values of the target: radial distance, radial speed, horizontal distance and horizontal speed respectively. In order to ensure the accuracy of trajectory prediction, the trajectory pre-processing is carried out by means of threshold filtering and smooth filtering, and the Markov prediction model is established after the data preprocessing completed, then the trajectory prediction is finally achieved. In this paper, the Markov model is used as a sample to predict the target trajectory by predicting the four eigenvalues of the actual data. The results show that the Markov model is used to realize the target trajectory prediction of millimeter-wave radar detection with high accuracy, which can be applied to actual traffic detection.","PeriodicalId":227449,"journal":{"name":"2022 IEEE Conference on Telecommunications, Optics and Computer Science (TOCS)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134131280","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

Stock price prediction based on multifactorial linear models and machine learning approaches 基于多因子线性模型和机器学习方法的股票价格预测

2022 IEEE Conference on Telecommunications, Optics and Computer Science (TOCS) Pub Date : 2022-12-11 DOI: 10.1109/TOCS56154.2022.10016086

Guanlan Shao

{"title":"Stock price prediction based on multifactorial linear models and machine learning approaches","authors":"Guanlan Shao","doi":"10.1109/TOCS56154.2022.10016086","DOIUrl":"https://doi.org/10.1109/TOCS56154.2022.10016086","url":null,"abstract":"With the development of economic and algorithmic models, stock price prediction has attracted more and more attention. This paper will investigate the stock forecasting based on multiple factors linear models and machine learning scenarios including four methods: multiple linear regression, exponential weighted moving average (EWMA), extreme gradient advance (XGBoost) and long-term short-term memory (LSTM). Three listed companies of Chinese market are selected from each of the following industries (total of nine companies) information technology, banking finance and catering and hotel. Besides, 730 daily market data is retrieved from January 1, 2019 to December 31, 2021. By using 18 factors with both daily market factors and technical factors to jointly predict the closing prices of these 9 stocks, the prediction effect of multiple linear regression model is better than XGBoost and LSTM in the case of less data. In other words, XGBoost and LSTM cannot give full play to their own advantages under this background. The research of this paper further explores the applicable scenarios of different models and these results shed light on the related research of multi model prediction of stock closing price.","PeriodicalId":227449,"journal":{"name":"2022 IEEE Conference on Telecommunications, Optics and Computer Science (TOCS)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132963874","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

An Improved COSMIC Software Evaluation Method 一种改进的COSMIC软件评价方法

2022 IEEE Conference on Telecommunications, Optics and Computer Science (TOCS) Pub Date : 2022-12-11 DOI: 10.1109/TOCS56154.2022.10016147

Fang Wang, Futan Ma, Guoxing Song, Jianqian Zhang

{"title":"An Improved COSMIC Software Evaluation Method","authors":"Fang Wang, Futan Ma, Guoxing Song, Jianqian Zhang","doi":"10.1109/TOCS56154.2022.10016147","DOIUrl":"https://doi.org/10.1109/TOCS56154.2022.10016147","url":null,"abstract":"Under the background of the Internet era, there are many kinds of software applicable to various business scenarios everywhere. How to evaluate the scale of a software is not only related to the investment of software development time, but also affects the investment of capital and personnel in software development. At present, the mainstream software scale evaluation method is the full Function Point analysis (COSMIC-FFP) proposed by the International Association for Universal Software Measurement. COSMIC software evaluation method through the retrieval of all the data movement process, each data movement process as a function point (CFP), and finally through the statistics of the number of CFP to get the size of the entire software measurement this paper proposes an improved COSMIC software evaluation method: according to the software needs description, grammar and syntax. For the relatively fixed language features such as parts of speech, we should develop corresponding segmentation tagging and error filtering rules, introduce natural language processing ideas to process software function points, and build local rule base to weaken the over-dependence of appraisers on rule guide and reduce the difficulty of getting started. Experiments and actual evaluation show that the improved method in this paper not only improves the accuracy, but also improves the time efficiency more obviously.","PeriodicalId":227449,"journal":{"name":"2022 IEEE Conference on Telecommunications, Optics and Computer Science (TOCS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130819082","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

Advances of Gate Stack Technology in MOSFETs mosfet中栅极堆叠技术的研究进展

2022 IEEE Conference on Telecommunications, Optics and Computer Science (TOCS) Pub Date : 2022-12-11 DOI: 10.1109/TOCS56154.2022.10015955

Lefu Xie

引用次数: 0

A review of motion control methods and bionic control theory for quadruped robots 四足机器人运动控制方法及仿生控制理论综述

2022 IEEE Conference on Telecommunications, Optics and Computer Science (TOCS) Pub Date : 2022-12-11 DOI: 10.1109/TOCS56154.2022.10016139

Liang Zhaoxi

引用次数: 0

Parameter Identification of Stylized Free-lane-changing Bezier Model Based on Behavioral Clustering 基于行为聚类的程式化自由变道Bezier模型参数辨识

2022 IEEE Conference on Telecommunications, Optics and Computer Science (TOCS) Pub Date : 2022-12-11 DOI: 10.1109/TOCS56154.2022.10016202

Huitong Fu, Zhichao Xing, Dong Cui, Xianming Meng, Hui Zhang, Jingyan Zhou, Zhonghao Ji

{"title":"Parameter Identification of Stylized Free-lane-changing Bezier Model Based on Behavioral Clustering","authors":"Huitong Fu, Zhichao Xing, Dong Cui, Xianming Meng, Hui Zhang, Jingyan Zhou, Zhonghao Ji","doi":"10.1109/TOCS56154.2022.10016202","DOIUrl":"https://doi.org/10.1109/TOCS56154.2022.10016202","url":null,"abstract":"In order to realize the identification of driving style differences in intelligent vehicle free lane changing decision in heterogeneous traffic flow, a driving behavior data collection system was built in this research to obtain the natural driving data of multi-attribute drivers, and the free lane changing behaviors of heterogeneous data were mined based on multi-constraint extraction method. The time frequency characteristic parameters associated with free lane changing were extracted, and the conservative, robust and radical behavior clustering were completed based on PCA and K-means methods. The bezier curve was selected for modeling, and the stylized behavior data were input based on the genetic algorithm for parameters identification. Finally, three types of stylized free lane changing models were obtained. The stylized identification models were evaluated by random lane changing behavior data. The RMSPE value of the model can be obtained, and the prediction accuracy of stylized bezier curve was better than the that of the random lane change curve.","PeriodicalId":227449,"journal":{"name":"2022 IEEE Conference on Telecommunications, Optics and Computer Science (TOCS)","volume":"117 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115591471","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 key technologies of power grid operation resource allocation based on Internet of Things 基于物联网的电网运行资源配置关键技术研究

2022 IEEE Conference on Telecommunications, Optics and Computer Science (TOCS) Pub Date : 2022-12-11 DOI: 10.1109/TOCS56154.2022.10016195

Riquan Yao, S. Jin, Yingqun Fei, Lifeng Fang

{"title":"Research on key technologies of power grid operation resource allocation based on Internet of Things","authors":"Riquan Yao, S. Jin, Yingqun Fei, Lifeng Fang","doi":"10.1109/TOCS56154.2022.10016195","DOIUrl":"https://doi.org/10.1109/TOCS56154.2022.10016195","url":null,"abstract":"The explosive growth of heterogeneous and multi-source data information has also spawned the demand for diversification and decolonialization of the Internet of Things business. In view of the current application mode of Internet of Things technology in power transmission and transformation operation and maintenance, this paper innovatively proposes to take the substation operation and maintenance based on Internet of Things technology as the research object, and to build a operation and maintenance resource allocation model in the Internet of Things environment as the core goal of research. This paper proposes an IoT network system based on the SOM algorithm. This paper aims to achieve the maximum intelligent acquisition and Internet of Things awareness of operational resource information in the process of power grid operation and maintenance in actual engineering. The superiority and credibility of SOM neural network and Internet of Things technology in engineering information acquisition and distribution perception are verified through simulation and optimization.","PeriodicalId":227449,"journal":{"name":"2022 IEEE Conference on Telecommunications, Optics and Computer Science (TOCS)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115690066","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

Simulation and Research of Liquid Level Cascade Control System 液位串级控制系统的仿真与研究

2022 IEEE Conference on Telecommunications, Optics and Computer Science (TOCS) Pub Date : 2022-12-11 DOI: 10.1109/TOCS56154.2022.10016096

Xinhua Li, Q. Lu, Yanli Zhang

引用次数: 2