发布求助
文献互助 智能选刊 最新文献

2019 IEEE 8th Data Driven Control and Learning Systems Conference (DDCLS)最新文献

筛选
英文 中文
A Feature Extraction Method Based on Multi-rhythmic and Co-space Modes for P300 Potential 基于多节奏共空间模式的P300电位特征提取方法
2019 IEEE 8th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2019-05-01 DOI: 10.1109/DDCLS.2019.8908941
Guo Chen, Xin Deng, Yun Tang, Jianxun Mi, Danni Li, Kaiwei Sun
{"title":"A Feature Extraction Method Based on Multi-rhythmic and Co-space Modes for P300 Potential","authors":"Guo Chen, Xin Deng, Yun Tang, Jianxun Mi, Danni Li, Kaiwei Sun","doi":"10.1109/DDCLS.2019.8908941","DOIUrl":"https://doi.org/10.1109/DDCLS.2019.8908941","url":null,"abstract":"In order to extract the effective features of EEG data based on P300 potential and improve the classification accuracy of brain-computer interface (BCI) system, a novel method from spatial and frequency domain is proposed in this paper. That is, the multi-rhythm signal and Common Spatial Pattern (CSP) are combined to extract the feature of P300 potential. Meanwhile, this paper uses the elastic networks as classifier which combines with $l_{1}$ norm and $l_{2}$ norm that not only makes the coefficients sparse, but also avoids losing the inhere t structure among samples from the same class. In this paper, the public EEG data set is used to verify the proposed method and by comparing the traditional CSP method. The experimental results show that the new method provides more frequency-space-related feature information increased by 4.8% compared with the traditional CSP method. It indicates that the proposed method achieves the good performance for the P300 EEG analysis.","PeriodicalId":6699,"journal":{"name":"2019 IEEE 8th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"16 1","pages":"304-309"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89345760","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
Attitude Tracking Control of 3-DOF Helicopter Based on Disturbance Observer 基于扰动观测器的三自由度直升机姿态跟踪控制
2019 IEEE 8th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2019-05-01 DOI: 10.1109/DDCLS.2019.8909003
Liang Liu, J. Wang, B. Xiao
{"title":"Attitude Tracking Control of 3-DOF Helicopter Based on Disturbance Observer","authors":"Liang Liu, J. Wang, B. Xiao","doi":"10.1109/DDCLS.2019.8909003","DOIUrl":"https://doi.org/10.1109/DDCLS.2019.8909003","url":null,"abstract":"Based on the disturbance observer design approach, this paper deals with the attitude tracking control problem for a 3-DOF helicopter with uncertainty and external disturbance. Firstly, the disturbance observers are used to estimate the uncertainty and the external disturbance of the 3-DOF helicopter. Then, with the aid of the estimations and backstepping design method, the new nonlinear tracking controllers with disturbance compensations are proposed. And, it is verified that the resulting closed-loop 3-DOF helicopter system is asymptotically stable by employing Lyapunov stability theory. Finally, simulation results demonstrate the effectiveness of the proposed design approach.","PeriodicalId":6699,"journal":{"name":"2019 IEEE 8th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"8 1","pages":"610-614"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87318119","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: 3
Prediction of Stock Trading Signal Based on Multi-indicator Channel Convolutional Neural Networks 基于多指标通道卷积神经网络的股票交易信号预测
2019 IEEE 8th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2019-05-01 DOI: 10.1109/DDCLS.2019.8908881
Zhen Yang, K. Hao, Xin Cai, Lei Chen, L. Ren
{"title":"Prediction of Stock Trading Signal Based on Multi-indicator Channel Convolutional Neural Networks","authors":"Zhen Yang, K. Hao, Xin Cai, Lei Chen, L. Ren","doi":"10.1109/DDCLS.2019.8908881","DOIUrl":"https://doi.org/10.1109/DDCLS.2019.8908881","url":null,"abstract":"Stock forecasting has always been a tempting and challenging problem in the field of financial research. Recently, convolutional neural networks have been used to classify trading signals of stock, but different indicator rankings will generate different images when generating data picture. A multi-indicator channel convolutional neural network (MICNN) is proposed to avoid the uncertainty of image generation. The test results are better than MLP and show that the proposed model has good classification performance, and the results of the simulated trading prove that the trading signals predicted by our method have practical value.","PeriodicalId":6699,"journal":{"name":"2019 IEEE 8th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"20 1","pages":"912-917"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86936692","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
A Novel Multivariable Nonlinear Time Series Prediction Method for APSO-Elman Network 一种新的APSO-Elman网络多变量非线性时间序列预测方法
2019 IEEE 8th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2019-05-01 DOI: 10.1109/DDCLS.2019.8909014
Kexian Ren, Yongjian Wang, Bo Yang, Hong-guang Li
{"title":"A Novel Multivariable Nonlinear Time Series Prediction Method for APSO-Elman Network","authors":"Kexian Ren, Yongjian Wang, Bo Yang, Hong-guang Li","doi":"10.1109/DDCLS.2019.8909014","DOIUrl":"https://doi.org/10.1109/DDCLS.2019.8909014","url":null,"abstract":"Elman neural network is a local dynamic neural network with good approximation fitting ability, which is suitable for the prediction of complex nonlinear time series models. When multi-variable, multi-step nonlinear industrial process prediction is involved. However, the traditional Elman neural network learning parameters are too slow, difficult to find an optimal parameter. To overcome the weakness of the traditional Elman neural network, this paper proposed a new adaptive particle swarm optimization Elman (APSO-Elman) neural network, which can achieve better results for nonlinear, multi-step, multivariate time series prediction. Find the optimal weight parameters for the neural network. Firstly, the data mining method is applied to select the appropriate correlation variables, then the APSO-Elman algorithm is used to find the optimal neural network weight parameters. To verify the effectiveness of the method, the non-isothermal continuous tank stirred reactor discharge concentration is used to predict. Compared with the traditional Elman neural network and PSO-Elman network, the results show that the method can accelerate the learning rate of parameters and find the optimal parameters, thus improving the accuracy of discharge concentration prediction.","PeriodicalId":6699,"journal":{"name":"2019 IEEE 8th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"24 1","pages":"218-224"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86594315","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
Fault Diagnosis Based on Sensitive SVD and Gaussian Process Latent Variable Model 基于敏感SVD和高斯过程潜变量模型的故障诊断
2019 IEEE 8th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2019-05-01 DOI: 10.1109/ddcls.2019.8909071
Yang Gao, Yugang Fan, Qingyu Zhang
{"title":"Fault Diagnosis Based on Sensitive SVD and Gaussian Process Latent Variable Model","authors":"Yang Gao, Yugang Fan, Qingyu Zhang","doi":"10.1109/ddcls.2019.8909071","DOIUrl":"https://doi.org/10.1109/ddcls.2019.8909071","url":null,"abstract":"To solve the problems that the system running state feature in fault diagnosis is sometimes masked by noise and its high dimensionality decreases the fault recognition degree. A fault diagnosis method based on Sensitive Singular Value Decomposition (Sensitive SVD) and Gaussian Process Latent Variable Model (GPLVM) is proposed. The method firstly performs Sensitive SVD analysis on the vibration signal, extracts various time domain features from the reconstructed signal, constructs a high-dimensional feature set, and uses GPLVM to reduce the dimensionality, and then use the reduced feature to establish the Extreme Learning Machine (ELM) fault diagnosis model. The rolling bearing fault detection test shows that the proposed method can effectively reduce the redundancy of features, and the established fault diagnosis model has higher identification accuracy.","PeriodicalId":6699,"journal":{"name":"2019 IEEE 8th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"9 1","pages":"787-793"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89866243","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
Visual Detection System of Automotive Parts Attitude Based on Deep Learning 基于深度学习的汽车零部件姿态视觉检测系统
2019 IEEE 8th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2019-05-01 DOI: 10.1109/DDCLS.2019.8909036
Jiaxu Zhang, Shaolin Hu, Haoqiang Shi
{"title":"Visual Detection System of Automotive Parts Attitude Based on Deep Learning","authors":"Jiaxu Zhang, Shaolin Hu, Haoqiang Shi","doi":"10.1109/DDCLS.2019.8909036","DOIUrl":"https://doi.org/10.1109/DDCLS.2019.8909036","url":null,"abstract":"In the automobile assembly process, pose detection technology is the key technology in the assembly system, which plays an important role in the assembly work and will directly affect the assembly results. In order to improve the detection intelligence and accuracy, the deep learning vision technology is applied to the attitude measurement of automotive parts assembly, and a method of extracting key points by deep learning is proposed. Different from the traditional methods, the deep convolutional network has strong robustness and versatility. Therefore, this paper proposes a joint detection method for double convolutional networks. First, the deep convolutional network is used to predict the key points of the part. Then, the recursive convolutional neural network is used to optimize the prediction result. Finally, the key point coordinates are substituted into the PnP algorithm to check whether the part pose conforms to the standard. The simulation results show that the method can accurately realize the target attitude detection.","PeriodicalId":6699,"journal":{"name":"2019 IEEE 8th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"1 1","pages":"918-922"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89624639","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
Characteristics of Fusion Temperature of Fly Ashes Generated by the Combustion of Tobacco Rod and Lignite 烟叶与褐煤燃烧产生的飞灰熔合温度特性
2019 IEEE 8th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2019-05-01 DOI: 10.1109/DDCLS.2019.8909042
Yingchun Liu, Hao Zhang, S. Qing, Aimin Zhang, Zhumei Luo, Rong Zhao
{"title":"Characteristics of Fusion Temperature of Fly Ashes Generated by the Combustion of Tobacco Rod and Lignite","authors":"Yingchun Liu, Hao Zhang, S. Qing, Aimin Zhang, Zhumei Luo, Rong Zhao","doi":"10.1109/DDCLS.2019.8909042","DOIUrl":"https://doi.org/10.1109/DDCLS.2019.8909042","url":null,"abstract":"Fly ashes, as a type of solid wastes, has been widely recycled recently. Its characteristic is directly related to the temperature of the hearth in which it has been heated. The constituents and forms of the fly ashes may vary in the specific reaction atmosphere and temperature. In this paper, the X-ray diffraction (Xrd) and the scanning electron microscope (SEM) were applied to observe the mineral form and crystal components of the fly ashes generated by the combustion of tobacco rod and lignite. The results showed that: the fusion temperature of the fly ashes rised with the increase of the CaO content and the fusion temperature of the fly ashes in the oxidation atmosphere was about 50°C higher than that in the reducing atmosphere. Through the entire process, the fusion temperature of the fly ashes initially rises with the increase in the percentage of the residual carbon, then decreases and in the end it levels off. The results from this research work can be used as the guidelines for the reutilization of fly ashes in industrial production.","PeriodicalId":6699,"journal":{"name":"2019 IEEE 8th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"190 1","pages":"718-722"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74182106","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
Aerodrome Clearance Monitoring and Management Based on Multi-Source High Resolution Remote Sensing Data 基于多源高分辨率遥感数据的机场间隙监测与管理
2019 IEEE 8th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2019-05-01 DOI: 10.1109/DDCLS.2019.8908907
Yubin Xu, Yan Ma, Jing Guo, Xu-hui Wang, Shasha Liu, Li Ma
{"title":"Aerodrome Clearance Monitoring and Management Based on Multi-Source High Resolution Remote Sensing Data","authors":"Yubin Xu, Yan Ma, Jing Guo, Xu-hui Wang, Shasha Liu, Li Ma","doi":"10.1109/DDCLS.2019.8908907","DOIUrl":"https://doi.org/10.1109/DDCLS.2019.8908907","url":null,"abstract":"FAA and ICAO have clear specification for aerodrome clearance management, which is vital for ensuring safe takeoff, flight and landing to aircrafts. This work proposed a new method to identify obstacles and evaluate potential hazards, which will make great contribution for clearance management and help mitigate possible risk in aviation security framework. This came up with new fully automatic methodology to detect environmental building change and OISs surface penetration based on multi-source high resolution remote sensing data. Shape extraction and classification of obstacles will be figured out from stereo paired images. This kind of clearance remote spatial patrol can be done every a few days, which is very suitable for wide area where is huge difficult to reach and human patrol pattern may miss. The application in Changshui International Airport proved to be very effective strategy to update obstacles database and manage clearance. More importantly, it helps guarantee aerodrome terminal operation safety.","PeriodicalId":6699,"journal":{"name":"2019 IEEE 8th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"12 1","pages":"871-875"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74411997","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 Intelligent Supervision System of Environmental Pollution in Industrial Park 工业园区环境污染智能监控系统
2019 IEEE 8th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2019-05-01 DOI: 10.1109/DDCLS.2019.8908925
L. xilinx Wang, Bo Han, Jiping Xu, Zhiyao Zhao, Xiaoyi Wang
{"title":"An Intelligent Supervision System of Environmental Pollution in Industrial Park","authors":"L. xilinx Wang, Bo Han, Jiping Xu, Zhiyao Zhao, Xiaoyi Wang","doi":"10.1109/DDCLS.2019.8908925","DOIUrl":"https://doi.org/10.1109/DDCLS.2019.8908925","url":null,"abstract":"In order to solve the present problem of China's industrial park which caused by environmental pollution, this paper adopts axios interface technology, Web service technology, node.js technology, developing an intelligent supervision system for environmental pollution in industrial parks. Through this system, which can achieve the function of remote real-time monitoring, forecasting and early warning, decision analysis of various environmental pollutants discharged by enterprises and emergency management of environmental pollution emergencies in industrial parks. The system can obtain real-time environmental pollutant discharge data of each enterprise through monitors installed in industrial parks, according to the obtained data using radial basis function (RBF) neural network algorithm to predict the trend of environmental pollutants of various enterprises. Also, according to the environmental pollutants data we get for each enterprise risk analysis, then the risk analysis results for decision-making of the enterprise. What's more, we use all the results to be displayed visually.","PeriodicalId":6699,"journal":{"name":"2019 IEEE 8th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"12 1","pages":"1160-1165"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72839763","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
Empirical Wavelet Transform and Its Application in Fault Feature Extraction of Rolling Bearings 经验小波变换及其在滚动轴承故障特征提取中的应用
2019 IEEE 8th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2019-05-01 DOI: 10.1109/DDCLS.2019.8908872
Pengcheng Yin, Xin Xiong
{"title":"Empirical Wavelet Transform and Its Application in Fault Feature Extraction of Rolling Bearings","authors":"Pengcheng Yin, Xin Xiong","doi":"10.1109/DDCLS.2019.8908872","DOIUrl":"https://doi.org/10.1109/DDCLS.2019.8908872","url":null,"abstract":"Rolling bearing is one of the most widely used rotating machinery. For easy damage, it is a main problem in its fault diagnosis. Proposed in 2013, The Empirical Wavelet Transform (EWT), an adaptive signal decomposition method combining theoretical background of wavelet transform and the adaptivity of EMD. The theory of EWT is introduced in this essay and EWT is used in the fault feature extraction of rolling bearings for the decomposition of original signal. With kurtosis criterion, desired results are got. Compared with EMD, problems in mode mixing and illusive components is solved by EWT, which has fewer components and better efficiency in analysis.","PeriodicalId":6699,"journal":{"name":"2019 IEEE 8th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"2012 1","pages":"855-860"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73599109","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: 3
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：604180095
Book学术官方微信