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检索条件"任意字段=7th IEEE Data Driven Control and Learning Systems Conference, DDCLS 2018"

共 474 条记录，以下是161-170 订阅

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Soft-Sensing Development Using Adaptive PSO Optimization Based Multi-Kernel ELM with Error Feedback 7

Soft-Sensing Development Using Adaptive PSO Optimization Bas...

引用

ieee 7th data driven control and learning systems conference (ddcls)

作者： Xu, Yuan Du, Qiang Zhang, Mingqing Zhu, Qunxiong He, Yanlin Beijing Univ Chem Technol Coll Informat Sci & Technol Beijing 100029 Peoples R China Minist Educ China Engn Res Ctr Intelligent PSE Beijing 100029 Peoples R China

ISBN: (纸本)9781538626184

It is very hard to measure some process variables directly in actual industrial processes, so a soft senor model using adaptive particle swarm optimization (PSO) optimization based multi-kernel ELM with error feedback is proposed in this paper. Firstly, multi-kernel ELM is constructed by adding gaussian and polynomial kernel function to ameliorate the overfitting problem in traditional ELM. Secondly, we propose an adaptive PSO (APSO) for ameliorating the low efficiency problem in the later period of PSO method by adding mutation operator. When given parameter reaches a threshold, the mutation operator adaptively adjusts the position of the particle. Also, the proportion of two kernel functions and the kernel parameters in training process are obtained by APSO. In each iteration, the training error is back propagated to the hidden layer as the co-outputs of hidden layer for further improving the accuracy and stability of the model. Finally, a simulation experiment on the purified terephthalic acid (PTA) solvent system is made to verify the modeling accuracy and optimized performances. the evaluation result demonstrates that the proposed method can provide higher accuracy and a more reliable soft senor model compared with other method.

关键词： Extreme learning machine (ELM) multi-kernel error feedback PSO purified terephthalic acid (PTA) solvent system

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Moving Object Real-time Detection and Tracking Method Based on Improved Gaussian Mixture Model 7

Moving Object Real-time Detection and Tracking Method Based ...

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ieee 7th data driven control and learning systems conference (ddcls)

作者： Zhu, Shanliang Gao, Xin Wang, Haoyu Xu, Guangwei Xie, Qiuling Yang, Shuguo Qingdao Univ Sci & Technol Sch Math & Phys Res Ctr Math Modeling Qingdao 266061 Peoples R China Qingdao Univ Sci & Technol Finance Off Qingdao 266061 Peoples R China Qingdao Univ Sci & Technol Sch Math & Phys Inst Intelligence Sci & Data Technol Qingdao 266061 Peoples R China

ISBN: (纸本)9781538626184

In order to improve the reliability of moving objects detection and tracking, this paper presents a method for moving object real-time detection and tracking based on Vibe and Gaussian mixture model (GMM). this method uses the "Virtual" background model that is trained by video sequence instead of the first frame image for background modeling. And then the foreground object is extracted based on the pixel classification. Finally, according to the morphological method, the clearer moving targets are conducted to realize the real-time detection and tracking. the experimental results show that, in comparison with the current mainstream background subtraction techniques, our approach effectively works on a wide range of complex scenarios, with faster detection speed and more reliable detection results.

关键词： moving object detection Vibe Gaussian mixture model pixel classification

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A Bidirectional Green Wave Band Method under Asymmetric Phase Sequence Mode based on Mobile Navigation data 7

A Bidirectional Green Wave Band Method under Asymmetric Phas...

引用

ieee 7th data driven control and learning systems conference (ddcls)

作者： Tan, Jiyuan Zhang, Ming Li, Honghai Guo, Weiwei Wang, Li North China Univ Technol Beijing Key Lab Urban Intelligent Traff Control T Beijing 100144 Peoples R China Minist Transport Beijing Res Inst Highway Beijing Peoples R China

ISBN: (纸本)9781538626184

With the continuous development of the city, traffic congestion is a serious problem. In order to reduce average delay and average numbers of stop, this paper proposed a bidirectional green wave band method under asymmetric phase sequence mode based on free-flow speed. the main idea to the method is to design a bidirectional wave band for arterial roads. Firstly, the different speed between each two intersections is considered and three speed calculation methods are proposed in this paper. then, intersections with asymmetric phase sequence are also mentioned and this method adjust the relative offset by set a random number which range of zero to the public cycle length. Finally, choose the maximum of all green wave bandwidths by using graphical way. In order to test the effectiveness of the arterial signal coordination method proposed in this paper, a simulation model is considered, where the performance indexes are the average delay and average numbers of stop. the simulation result shows that the method proposed in this paper can improve the traffic capacity by increasing bandwidth and reducing delay.

关键词： Traffic congestion Graphical method Trajectories Bidirectional green wave Speed

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Direction of Arrival Estimation Based on Generalized Reference Curve Model 7

Direction of Arrival Estimation Based on Generalized Referen...

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ieee 7th data driven control and learning systems conference (ddcls)

作者： Cui, Lizhi Bu, Xuhui Yang, Junqi Yang, Yi He, Weina Henan Polytech Univ Sch Elect Engn & Automat Henan Jiaozuo 454000 Peoples R China Henan Polytech Univ Key Lab Control Engn Henan Prov Henan Jiaozuo 454000 Peoples R China Pingdingshan Univ Sch Comp Henan Pingdingshan 467000 Peoples R China

ISBN: (纸本)9781538626184

Currently, the widely used methods for direction of arrival (DOA) estimation were constructed based on the subspace, such as Multiple Signal Classification (MUSIC) and Estimating Signal Parameter via Rotational Invariance Techniques (ESPRIT), which needed to know the number of sources in advance. In this paper, a new model based on the Generalized Reference Curve Model (GRCM) for the DOA estimation was proposed, which do not need to know the sources number in advance. And the comparison of the performance between the proposed model and the MUSIC model was given to demonstrate the effectiveness of our method. the algorithm of Multi-target Intermittent Particle Swarm Optimization (MIPSO) was adopted to solve the model proposed in this paper, and the performance of the MIPSO was analyzed through a simulation. the result shown that:(1) the GRCM was an effective model to solve the DOA estimation without prior knowledge of the sources number;(2) the MIPSO was an efficient algorithm to solve the DOA estimation with much shorter operation time and high precision.

关键词： direction of arrival uniform linear array generalized reference curve model multi-target intermittent particle swarm optimization

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Dynamic State Estimation Using Event-Trigger Master-Slave Nonlinear Filter for WAMS Applications 7

Dynamic State Estimation Using Event-Trigger Master-Slave No...

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ieee 7th data driven control and learning systems conference (ddcls)

作者： Yuan, Qing Zhang, Fengdi Gong, Hengheng Li, Luyu Li, Sen Liao, Xiaozhong Li, Zhen Liu, Xiangdong Beijing Inst Technol Sch Automat Beijing 100081 Peoples R China Beijing Inst Technol Key Lab Intelligent Control & Decis Complex Syst Beijing 100081 Peoples R China Beijing Aerosp Automat Control Inst Beijing Peoples R China Natl Key Lab Sci & Technol Aerosp Intelligence Co Beijing Peoples R China Beijing Inst Radio Measurement Beijing 100854 Peoples R China

ISBN: (纸本)9781538626184

the real-time state estimation becomes greatly important with the wide application of phasor measurement unit (PMU) in distributed generation (DG) for wide-area measurement systems (WAMS). In view of estimation, particle filter (PF) is capable of providing the best performance but at the cost of heavy computation burden. Besides, the growing grid size sustainably boosts the amount of data communication from PMU, causing the congestion. An event-trigger master-slave nonlinear filter (ET-MSNF) is proposed to guarantee the estimation accuracy and get the communication bandwidth relieved. the local slave filter at the generator node carries out the local estimation and event-trigger strategy using unscented transformation, which is identical to the center slave. the master filter at the center is designed using Monte Carlo method to improve the center's estimation accuracy by the cooperation with the center slave. Such master-slave filtering structure can fully utilize the computation capability both at the center and node. Simulation on the standard ieee 39-bus system verify the performance of ET-MSNF.

关键词： Event-trigger master-slave nonlinear filter unscented transformation particle filter wide-area measurement systems

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Iterative learning based model identification and state of charge estimation of lithium-ion battery 7

Iterative learning based model identification and state of c...

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7th ieee data driven control and learning systems conference, ddcls 2018

作者： Zhu, Qiao Xu, Mengren Zheng, Mengrqian School of Mechanical Engineering Southwest Jiaotong University Chengdu610031 China

ISBN: (纸本)9781538626184

this work focuses on the accurate identification of Lithium-ion battery's nonlinear parameters by using an iterative learning method. First, the 2nd-order RC model is introduced. then, when the battery repeatedly implements a discharging trial from SOC 100% to 0%, an iterative learning based recursive least square (IL-RLS) algorithm is presented to accurately identify the nonlinear parameters of the regression model. the essential idea of IL-RLS algorithm is to improve the current parameter estimations by learning the estimation errors of the previous trails. Notably, the IL-RLS algorithm needs to be implemented offline for the long-time repetitive trials, which is the price worth paying to accurately identify the nonlinear parameters. After that, the parameters are identified as the functions of SOC by using the IL-RLS, which are verified by comparing with the result of the classic identification method for current pulses. Finally, by using the classic extended Kalman filter (EKF) as well as the parameters identified by the IL-RLS to estimate the SOC, three dynamic operation conditions are given to show the efficiency of the IL-RLS, where all the SOC estimation errors are less than 2%. © 2018 ieee.

关键词： Lithium-ion batteries

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An Improved Stop and Go Model Considering Exhaust Emissions for Connected Vehicles 7

An Improved Stop and Go Model Considering Exhaust Emissions ...

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ieee 7th data driven control and learning systems conference (ddcls)

作者： Wang, Pangwei Ma, Yue Yu, Hongbin Wang, Li Zhang, Wei North China Univ Technol Beijing Key Lab Urban Intelligent Traff Control T Beijing 100144 Peoples R China China Acad Transportat Sci Beijing 100029 Peoples R China

ISBN: (纸本)9781538626184

Increasing vehicle ownership causes more and more serious urban traffic jam, meanwhile it also brings about much more idle time and exhaust emissions. the Stop and Go model is used to reduce stop time when vehicles drive at low speed status. With the development of connected vehicles, in this paper, an improved Stop and Go model is established considering low speed status of the leading vehicle and the following vehicle at the same time. Firstly, by combining the advantage of connected vehicles, the improved Stop and Go model chooses the minimum emissions as the control target. According to the emissions evaluation principle of Comprehensive Modal Emissions Model (CMEM), the objective function is established;secondly, in accordance with the actual traffic conditions and the operating conditions of the sample vehicle, the constraints are established;finally, the improved Stop and Go model is simulated based on Octave software. To prove the feasibility, we use CMEM to calculate the emissions of the following vehicle in the Stop and Go model and the linear Car-Following model. the results of exhaust emissions under two different models has been analyzed. Comparing with the linear Car-Following model, the HC emissions are reduced by 28%, CO emissions are reduced by 16%, and NOx emissions are reduced by 30%. therefore, the improved Stop and Go model can effectively reduce the emissions of vehicle exhaust.

关键词： Vehicle-to-Vehicle (V2V) communication Stop and Go model exhaust emissions connected vehicles

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A K-shell improved method for the importance of complex network nodes 7

A K-shell improved method for the importance of complex netw...

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7th ieee data driven control and learning systems conference, ddcls 2018

作者： Jianmin, Xing Jianqiang, Chen Xiuwen, Sun Xinli, Zhang Ruikun, Zhang School of Mathematics and Physics Qingdao University of Science and Technology Qingdao266061 China Institute of Intelligence Science and Data Technology School of Mathematics and Physics Qingdao University of Science and Technology Qingdao266061 China Research Center for Mathematical Modeling School of Mathematics and Physics Qingdao University of Science and Technology Qingdao266061 China

ISBN: (纸本)9781538626184

In this paper, a weighted k-shell method is proposed to further improve the distinction of node importance by taking advantage of the number of iterations and edge weights when the node is deleted. the weighted k-shell decomposition method is applied to simple networks and complex networks respectively. the simulation results show that the improved method has low computational complexity, high result resolution and high accuracy. © 2018 ieee.

关键词： Complex networks

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A K-shell Improved Method for the Importance of Complex Network Nodes

A K-shell Improved Method for the Importance of Complex Netw...

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ieee 7th data driven control and learning systems conference (ddcls)

作者： Xing Jianmin Chen Jianqiang Sun Xiuwen Zhang Xinli Zhang Ruikun Qingdao Univ Sci & Technol Sch Math & Phys Qingdao 266061 Peoples R China Qingdao Univ Sci & Technol Sch Math & Phys Inst Intelligence Sci & Data Technol Qingdao 266061 Peoples R China Qingdao Univ Sci & Technol Sch Math & Phys Res Ctr Math Modeling Qingdao 266061 Peoples R China

ISBN: (纸本)9781538626184

关键词： K-shell method Complex networks Computational complexity Node importance

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Structured Joint Sparse Principal Component Analysis for Fault Detection and Isolation 7

Structured Joint Sparse Principal Component Analysis for Fau...

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ieee 7th data driven control and learning systems conference (ddcls)

作者： Liu, Yi Zeng, Jiusun Xie, Lei Luo, Shihua Su, Hongye Zhejiang Univ Inst Cyber Syst & Control Hangzhou 310027 Zhejiang Peoples R China China Jiliang Univ Coll Metrol & Measurement Engn Hangzhou 310018 Zhejiang Peoples R China Jiangxi Univ Finance & Econ Sch Stat Nanchang 330013 Jiangxi Peoples R China

ISBN: (纸本)9781538626184

Principal component analysis (PCA) has been widely applied in process monitoring of modern industrial systems. PCA performs fault detection by mapping the process data into a low dimensional subspace and tracking the process behavior using T-2 and SPE statistics, whilst in fault isolation, it heavily relies on contribution plot or reconstruction based approaches. However, conventional methods based on contribution plot and reconstruction suffer from insufficient fault isolation capabilities. In order to improve the fault isolation performance, this article proposes a novel fault detection and isolation approach based on the Structured Joint Sparse PCA (SJSPCA). the objective function of SJSPCA involves two regularization terms: l(2,1) norm and the graph Laplacian. By imposing the l(2,1) norm term, SJSPCA is able to achieve row-wise sparsity, introducing the graph Laplacian regularization term can incorporate structured variable correlation information. In fault detection, conventional T-2 and SPE statistics are constructed to detect abnormal situations. Once a fault is detected, a two stage fault isolation strategy is considered and a score index is calculated for each variable. the row-sparsity property of l(2,1) norm ensures that the score indices associated to normal variables approach zero and the graph Laplacian constraint helps isolation of correlated faulty variables. the validity of SJSPCA in fault detection and isolation is illustrated by a process fault observed in an industrial blast furnace iron-making process.

关键词： Structured joint sparse principal component analysis Graph Laplacian Fault score Fault detection and isolation

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