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2022 IEEE 2nd International Conference on Data Science and Computer Application (ICDSCA)最新文献

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The Implied Volatility Surface Analysis Based Trading System 基于隐含波动面分析的交易系统
2022 IEEE 2nd International Conference on Data Science and Computer Application (ICDSCA) Pub Date : 2022-10-28 DOI: 10.1109/ICDSCA56264.2022.9987792
Guoxiang Guo, Y. Qi, Sirui Lai, J. Yen
{"title":"The Implied Volatility Surface Analysis Based Trading System","authors":"Guoxiang Guo, Y. Qi, Sirui Lai, J. Yen","doi":"10.1109/ICDSCA56264.2022.9987792","DOIUrl":"https://doi.org/10.1109/ICDSCA56264.2022.9987792","url":null,"abstract":"Volatility is a crucial factor in option pricing models. The implied volatility is the estimated volatility from market trades and represents market sentiment in recent research. The implied volatility surface (IVS) based market analysis is also gathering more attention for its satisfying regression performance in risk management and related tasks. In this research, we develop an industrial application of the market trading system based on Support Vector Regression (SVR) and implement simulated trading through backtesting. According to the SPY option historical data experiment results, considering appropriate transaction cost, the system reaches satisfying performance in the fluctuating market.","PeriodicalId":416983,"journal":{"name":"2022 IEEE 2nd International Conference on Data Science and Computer Application (ICDSCA)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116666960","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
Analysis of Thermal and Electrolytic Coupling Characteristics of Typical Thermal Power Plants in China 中国典型火电厂热电耦合特性分析
2022 IEEE 2nd International Conference on Data Science and Computer Application (ICDSCA) Pub Date : 2022-10-28 DOI: 10.1109/ICDSCA56264.2022.9988039
Wen Sun
{"title":"Analysis of Thermal and Electrolytic Coupling Characteristics of Typical Thermal Power Plants in China","authors":"Wen Sun","doi":"10.1109/ICDSCA56264.2022.9988039","DOIUrl":"https://doi.org/10.1109/ICDSCA56264.2022.9988039","url":null,"abstract":"In order to improve the flexibility of the thermal power unit, improve the peak regulation and heat supply regulation capacity of the power plant, and promote the consumption of new energy, this paper takes a 350MW unit in China as the research object. 4 kinds of thermo-decoupling technical schemes, such as absorption heat pump and compression heat pump, are calculated to calculate the change of the maximum heat supply and electric load rate of the unit after thermo-decoupling of each scheme. The results show that after decoupling, the maximum heat supply of the units in each scheme can be increased by 174MW, 136.18MW, 168.37MW, and 38MW respectively; under the original maximum heat supply load, the minimum electrical load rate is reduced to 44.29%, 73.29%, 73.70%, and 80.57%. The low-pressure cylinder zero output technology has the best effect, the maximum heat supply of the unit is increased the most, and the electrical load rate is also reduced the most.","PeriodicalId":416983,"journal":{"name":"2022 IEEE 2nd International Conference on Data Science and Computer Application (ICDSCA)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127251882","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
Electroencephalogram and Electrocardiogram in Human-Computer Interaction 人机交互中的脑电图和心电图
2022 IEEE 2nd International Conference on Data Science and Computer Application (ICDSCA) Pub Date : 2022-10-28 DOI: 10.1109/ICDSCA56264.2022.9988056
Peiheng Li, Yicheng Qian, Nuo Si
{"title":"Electroencephalogram and Electrocardiogram in Human-Computer Interaction","authors":"Peiheng Li, Yicheng Qian, Nuo Si","doi":"10.1109/ICDSCA56264.2022.9988056","DOIUrl":"https://doi.org/10.1109/ICDSCA56264.2022.9988056","url":null,"abstract":"Electroencephalogram (EEG) and Electrocardiogram (ECG) have been widely used in clinical diagnosis and have shown their potential in Human-Computer Interaction (HCI). EEG and ECG contain signals that can directly reveal people's activity neurologically and decode and transfer for further physical monitoring and external control. This paper firstly summarizes heavily used methods of EEG signal process in HCI, which also applies to the ECG process. Then, we reviewed typical applications for EEG in HCI, including the TTD system, P300, and Graz for brain-computer interface and emotion recognition. We conclude ECG classification and acquisition methods and ECG application in HCI, including biometric identification, game input, and medical nursing. Finally, integrating EEG and ECG, there are HCI applications like accurate emotion recognition, physiological monitoring, disease diagnosis, and portable wearable device. In addition, we present the HCI application for Electromyogram (EMG) in gesture, handwriting recognition, and Electrooculogram (EOG) in password security, cursor system, and eye-writing.","PeriodicalId":416983,"journal":{"name":"2022 IEEE 2nd International Conference on Data Science and Computer Application (ICDSCA)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127363459","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 Flood Disaster Risk Assessment Based on Random Forest Algorithm 基于随机森林算法的洪水灾害风险评估研究
2022 IEEE 2nd International Conference on Data Science and Computer Application (ICDSCA) Pub Date : 2022-10-28 DOI: 10.1109/ICDSCA56264.2022.9987936
H. Cai
{"title":"Research on Flood Disaster Risk Assessment Based on Random Forest Algorithm","authors":"H. Cai","doi":"10.1109/ICDSCA56264.2022.9987936","DOIUrl":"https://doi.org/10.1109/ICDSCA56264.2022.9987936","url":null,"abstract":"In flood disaster risk assessment, disaster-pregnant environments, disaster-bearing bodies, and disaster-causing factors are the core categories of risk assessment indicators. A flood disaster risk assessment model based on the random forest algorithm can be constructed by manually identifying the samples and organizing the training data set using the Bagging method. SVM can be selected as a control model for verification to evaluate the model performance further. According to the evaluation of the importance of various influencing factors, it can be found that precipitation, flood duration, and soil moisture content in the local environment are the core factors for evaluating flood disaster risk. In order to cope with the small amount of data for high disaster risk levels, this paper uses the cutoff mechanism in $mathbf{R}$ language to correct the random forest results in the voting stage and obtains good results. The research in this paper provides a new idea based on artificial intelligence for flood disaster risk assessment.","PeriodicalId":416983,"journal":{"name":"2022 IEEE 2nd International Conference on Data Science and Computer Application (ICDSCA)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124944975","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 Identification Method of Sorghum Varieties Based on Machine Learning 基于机器学习的高粱品种识别方法研究
2022 IEEE 2nd International Conference on Data Science and Computer Application (ICDSCA) Pub Date : 2022-10-28 DOI: 10.1109/ICDSCA56264.2022.9988550
Shoushan Chen, Ziyi Song, Hongyan Xu
{"title":"Research on Identification Method of Sorghum Varieties Based on Machine Learning","authors":"Shoushan Chen, Ziyi Song, Hongyan Xu","doi":"10.1109/ICDSCA56264.2022.9988550","DOIUrl":"https://doi.org/10.1109/ICDSCA56264.2022.9988550","url":null,"abstract":"Sorghum varieties are closely related to sorghum yield. To achieve rapid identification of sorghum seed varieties, a sorghum variety recognition model based on machine learning was proposed. The morphological features of three kinds of sorghum seed hyperspectral images are extracted by pruning and segmentation, then data features are analyzed and dimensioned by principal component analysis, finally, SVM classifier is used to identify sorghum seed varieties, and high accuracy is achieved.","PeriodicalId":416983,"journal":{"name":"2022 IEEE 2nd International Conference on Data Science and Computer Application (ICDSCA)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124945435","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 Panoramic Fault Simulation Method of Electric Power Communication Transmission Network 电力通信传输网络全景故障仿真方法研究
2022 IEEE 2nd International Conference on Data Science and Computer Application (ICDSCA) Pub Date : 2022-10-28 DOI: 10.1109/ICDSCA56264.2022.9988498
Lizhuo Geng, Xuejie Hao, Lu Liu, Feng Gao
{"title":"Research on Panoramic Fault Simulation Method of Electric Power Communication Transmission Network","authors":"Lizhuo Geng, Xuejie Hao, Lu Liu, Feng Gao","doi":"10.1109/ICDSCA56264.2022.9988498","DOIUrl":"https://doi.org/10.1109/ICDSCA56264.2022.9988498","url":null,"abstract":"With the rapid development of electric power system, it is urgent to find out an effective and flexible transmission network fault simulation method to improve the fault analysis and handling competence of communication network operation and maintenance personnel. Aiming at the problems of current fault simulation solutions, this paper proposes a new panoramic fault simulation method of electric power communication transmission network. Firstly, the overall process of the method and simulation objects are introduced. Then the details of 4 main steps of the method are explained, such as equipment/cable simulation modeling building, fault simulation model building, simulation transmission network generation, fault loading the triggering. Finally, the application results of the method are briefly introduced. The method provides a new solution to panoramically recurrence of various types of electric power communication transmission faults, and supports the communication professionals to analyze the faults and improves their fault handling competence.","PeriodicalId":416983,"journal":{"name":"2022 IEEE 2nd International Conference on Data Science and Computer Application (ICDSCA)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123208271","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 Analysis of Tracking and Control Link Level in Launch Vehicle Based on STK 基于STK的运载火箭跟踪控制链路水平仿真分析
2022 IEEE 2nd International Conference on Data Science and Computer Application (ICDSCA) Pub Date : 2022-10-28 DOI: 10.1109/ICDSCA56264.2022.9988189
Qian He, G. Wu
{"title":"Simulation Analysis of Tracking and Control Link Level in Launch Vehicle Based on STK","authors":"Qian He, G. Wu","doi":"10.1109/ICDSCA56264.2022.9988189","DOIUrl":"https://doi.org/10.1109/ICDSCA56264.2022.9988189","url":null,"abstract":"The target feature analysis is essential for sea based launch vehicle tracking and control. The analysis method is performed with recognizing gain changes of telemetry antenna pattern in task usually and computing the automatic gain control (AGC) signal received by TT &C station manually. Aiming at the problems of low efficiency, complicated process and human errors, the method is discussed for a simulation analysis of tracking and control link level in launch vehicle based on STK, which elaborated emphatically for generating the electromagnetic field radiation pattern accord with STK format by launch vehicle antenna pattern. Compare the results of simulation and actual tracking by the launch vehicle in a flying, it indicates that the proposed method can satisfy the requirement in task and the result of simulation can be the reference by target feature analysis on launch vehicle.","PeriodicalId":416983,"journal":{"name":"2022 IEEE 2nd International Conference on Data Science and Computer Application (ICDSCA)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126646304","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
Sentiment Classification Model of Online Reviews Based on Word Features and Bi-LSTM 基于词特征和Bi-LSTM的在线评论情感分类模型
2022 IEEE 2nd International Conference on Data Science and Computer Application (ICDSCA) Pub Date : 2022-10-28 DOI: 10.1109/ICDSCA56264.2022.9988320
Jingxuan Hu
{"title":"Sentiment Classification Model of Online Reviews Based on Word Features and Bi-LSTM","authors":"Jingxuan Hu","doi":"10.1109/ICDSCA56264.2022.9988320","DOIUrl":"https://doi.org/10.1109/ICDSCA56264.2022.9988320","url":null,"abstract":"With the rapid development of e-commerce, many purchase and comment records are produced. Sentiment classification of commodity reviews is of great value for automatically monitoring bad reviews and assisting merchants in analyzing consumer feedback. At present, the Bi-LSTM model is representative of Chinese text sentiment classification, which can understand the semantic information in time sequence. However, due to the lack of processing lexical information, there is a problem that word vectors cannot highlight the information of sentiment words. Therefore, this paper proposes a sentiment classification model of Chinese product reviews based on word features and Bi-LSTM. The new model firstly uses Word2vec's CBOW model to train the word vectors, secondly uses an improved information gain algorithm with the word distribution and sentiment weights to calculate the amount of information, and finally uses the Naive Bayes model to classify the network classification results twice, which solves the problem that the basic Bi-LSTM model lacks understanding of lexical information. The experimental results show that the new model achieves better results relative to the basic Bi-LSTM model and can capture the sentiment information of the comments more accurately. In the test set, the accuracy rate reached 89.03%.","PeriodicalId":416983,"journal":{"name":"2022 IEEE 2nd International Conference on Data Science and Computer Application (ICDSCA)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114913211","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
Superstore Sales Forecasting Based on Elastic net Regression and BP Neural Networks 基于弹性网络回归和BP神经网络的超市销售预测
2022 IEEE 2nd International Conference on Data Science and Computer Application (ICDSCA) Pub Date : 2022-10-28 DOI: 10.1109/ICDSCA56264.2022.9988373
Nong Lili
{"title":"Superstore Sales Forecasting Based on Elastic net Regression and BP Neural Networks","authors":"Nong Lili","doi":"10.1109/ICDSCA56264.2022.9988373","DOIUrl":"https://doi.org/10.1109/ICDSCA56264.2022.9988373","url":null,"abstract":"Accurate sales forecasting is an important guide to business operations. It allows the operations back office to allocate resources to assist managers in making decisions. However, from the existing sales data of the store, it summarizes the change law of commodity sales, and dynamically predicts the sales in the future for a period of time according to the law. Moreover, this paper uses the elastic regression network model and BP neural network model to predict the sales of shops over a period of time. In order to improve the accuracy of the model, the model data is combined with one-hot coding. MAP, MPE and RMSE were chosen to be used as computational metrics for the evaluation for quantifying the accuracy of the mode. A comparison of the performance of the two models is made, which in turn has practical implications for companies to improve their promotions and increase their revenue.","PeriodicalId":416983,"journal":{"name":"2022 IEEE 2nd International Conference on Data Science and Computer Application (ICDSCA)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115208590","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
A Review of the Research Progress of Pruning Robots 修剪机器人研究进展综述
2022 IEEE 2nd International Conference on Data Science and Computer Application (ICDSCA) Pub Date : 2022-10-28 DOI: 10.1109/ICDSCA56264.2022.9988192
Haisen Zeng, Jia Yang, Nannan Yang, Jiawen Huang, Hao Long, Ying Chen
{"title":"A Review of the Research Progress of Pruning Robots","authors":"Haisen Zeng, Jia Yang, Nannan Yang, Jiawen Huang, Hao Long, Ying Chen","doi":"10.1109/ICDSCA56264.2022.9988192","DOIUrl":"https://doi.org/10.1109/ICDSCA56264.2022.9988192","url":null,"abstract":"Automation and robotics have been applied in various fields of agriculture and forestry. However, most production operations agriculture and forestry still rely on manual labor, among which pruning is one of the most labor-intensive operations. Therefore, robotic pruning is a potential long-term solution to labor shortages and the associated high costs. Although agricultural and forestry pruning is gradually mechanized, the successful application of pruning robotics still faces many challenges. This paper focuses on the core components and key technologies of pruning robots in agriculture and forestry, including machine vision, manipulators, end-effectors, path planning, and obstacle avoidance. Finally, the challenges and potential opportunities faced by pruning robots in agriculture and forestry are discussed.","PeriodicalId":416983,"journal":{"name":"2022 IEEE 2nd International Conference on Data Science and Computer Application (ICDSCA)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116076491","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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