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Traffic Congestion Prediction using Decision Tree, Logistic Regression and Neural Networks

IFAC-PapersOnLine 2020年第5期53卷 512-517页

作者： Tariku Sinshaw Tamir Gang Xiong Zhishuai Li Hao Tao Zhen Shen Bin Hu Heruye Mulugeta Menkir State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing 100049 China Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Chinese Academy of Sciences Dongguan 523808 China China Ship Development and Design Center Wuhan 430064 China Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing 100190 China Debremarkos University Institute of Technology Debremarkos 269 Ethiopia

Traffic congestion is a serious problem around the world and to a great extent influences urban communities in various manners including increased stress levels, delayed deliveries, fuel wastage, and monetary losses. Therefore, an accurate congestion prediction algorithm to limit these misfortunes is fundamental. This paper presents a comparative study of traffic congestion prediction systems including decision tree, logistic regression, and neural networks. Five days of traffic information (1,231,200 samples) are utilized to drive the prediction model. The TensorFlow and the Clementine machine learning platforms are used for data preprocessing, training, and testing of the model. The confusion matrix clears that decision tree has better prediction performance and leads the other two methods with accuracy (97%), macro-average precision (95%), macro-average recall (96%), and macro-average F1_score (96%) in the python programming environment. Moreover, performance of the three prediction models is verified in Clementine environment and decision tree outperforms all other models with an accuracy of 97.65%.

关键词： Confusion matrix Data preprocessing Python TensorFlow Clementine environment ITS

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3D Face Reconstruction System From A Single Photo Based On Regression Neural Network

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IFAC-PapersOnLine 2020年第5期53卷 71-76页

作者： Yatai Ji Keqiang Li Huaiyu Wu Gang Xiong Zhen Shen Xiuqin Shang Bangwen Xi The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China Department of Automation Tsinghua University Beijing 100084 China University of Chinese Academy of Sciences Beijing 100049 China The Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Chinese Academy of Sciences Donggguan 523808 China The Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing 100190 China

3D human face modeling is one of the most popular research directions in the field of computer stereo vision. On the one hand, the complex physiological structure of human face as well as various expressions and attitude changes bring great challenges to three-dimensional modeling, which makes the modeling method of human face have high research value and reference significance. On the other hand, 3D face reconstruction has a broad application prospect, and the application demand attracts more researchers to invest in it. Based on the 3DMM and 3DDFA method, this paper utilizes regression neural network to realize end-to-end face reconstruction. After that, we build a visualization program with the training model to realize face modeling based on a single face image of any pose or expression. It’s a 3D face reconstruction system which has functions such as face alignment, face rotation and so on.

关键词： face reconstruct 3DMM 3DDFA regression network

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Optimize Student Learning via Random Forest-Based Adaptive Narrative Game

Optimize Student Learning via Random Forest-Based Adaptive N...

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IEEE International Conference on Automation Science and Engineering (CASE)

作者： Ryan Hare Ying Tang Wei Cui Joleen Liang Department of Electrical and Computer Engineering Rowan University Glassboro USA State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Institute of Smart Education Qingdao Academy of Intelligent Industries Qingdao China Squirrel AI Learning Shanghai China

ISBN: (数字)9781728169040

ISBN: (纸本)9781728169057

This paper presents an adaptive narrative game system that focuses on sequential logic design. The system adapts a random forest machine learning model to estimate a student's current level of domain knowledge relative to the problem presented to him through his game-playing behavior data, such as time taken to find solutions, errors in solutions, and emotional indicators. Hints, prompts, and/or individualized lessons are then offered to the player to guide their learning in a positive and productive direction. Our preliminary pilot study demonstrates that the model can make accurate classifications, from which proper assistance can then be provided to individual students as they play.

关键词： Games Databases Forestry Education Problem-solving Presses Artificial intelligence

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Spacecraft High Accuracy Attitude control by Quaternion-Based Nonlinear Dynamic Inversion

Spacecraft High Accuracy Attitude Control by Quaternion-Base...

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第三十八届中国控制会议

作者： Jinhao Liu Jianying Yang Science and Technology on Aerospace Intelligent Control Laboratory The State Key Laboratory for Turbulence and Complex Systems Department of Mechanics and Engineering Science College of Engineering Peking University

Attitude control of spacecraft is an important operation that is general to every spacecraft. However, it is a challenging task due to the nonlinearity present in the spacecraft rotational equations when a certain requirement is demanded from a mission. Linearization can make system simple. But it is accurate only in small range. InfraRed Astronomy Satellite Swarm Interferometer(IRASSI) is a mission which demands an attitude accuracy better than 0.4 arcsec. Thus, in this paper, we check the feasibility of nonlinear dynamic inversion control method for single IRASSI satellite. Quaternion is chosen as the parameter for attitude description due to its singularity free property and avoidance of gimbal-lock phenomenon. In order to provide the shortest distance maneuver to save time and energy, the unwinding problem is also considered due to quaternion's 2:1 mapping.

关键词： Attitude control nonlinear dynamic inversion quaternion high accuracy

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Distributed optimization for continuous time multiple agents systems with unknown parameters

Distributed optimization for continuous time multiple agents...

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第三十八届中国控制会议

作者： Zilun Hu Jianying Yang Science and Technology on Aerospace Intelligent Control Laboratory The State Key Laboratory for Turbulence and Complex Systems Department of Mechanics and Engineering Science College of Engineering Peking University

This paper addresses a distributed convex optimization problem with objective functions for arbitrary order continuous time multiply agents systems with unknown parameters. In this paper, the control objective is not only to drive the multiply agents to reach a consensus, but also to cooperatively minimize the team objective function with consensus requirement. Different from the traditional optimization problems, in this paper, the proposed method is distributed, which means that the agent can only acquire the information of its neighbors' objective function through the network connection. Theoretical studies indicate that the proposed algorithms can minimize the team objective function and all agents will reach a consensus. Some simulation examples are presented to show the validity of the theoretical results.

关键词： Distributed optimization Adaptive control Multiply agents

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Trajectory Planning and Tracking control for Positioning of Planar Three-link Underactuated Manipulator

Trajectory Planning and Tracking Control for Positioning of ...

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Asian control Conference

作者： Zixin Huang Xuzhi Lai Pan Zhang Min Wu Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China School of Automation China University of Geosciences Wuhan China

ISBN: (纸本)9781728102634

This paper is concerned with the position control problem of the planar active-passive-active (APA) underactuated manipulator, whose dynamic constraint is mainly caused by the second-order nonholonomic constraint. First, the dynamic model of the system is established and the target angles of the three links are calculated by using differential evolution algorithm. Then, we present a trajectory planning and tracking control strategy to realize the control objective, which is to stabilize the end-point from any initial position to the target position. We plan two stage trajectories, the first of which is planned for the active links. When the the active links track the first stage trajectories, they can reach to their target angles. The second one is planned for the first active link based on the differential evolution algorithm. When the first active link tracks the second stage trajectory, it will back to its target angle eventually. Meantime, the passive link will be controlled to its target angle. Then, we design sliding mode variable structure controllers to make active links track the planned trajectories, which can make the all links reach to the their target angles. Finally, numerical simulation results illuminate the effectiveness of the proposed strategy.

关键词： Trajectory Manipulators Target tracking Position control Planning Heuristic algorithms Optimization

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Attenuation of PMSM Torque-Ripple Based on Combination of Equivalent-Input-Disturbance Approach and Sliding-Mode control

Attenuation of PMSM Torque-Ripple Based on Combination of Eq...

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Annual Conference of the IEEE Industrial Electronics Society

作者： Ruoyu Jiang Jinhua She Zhentao Liu Danyun Li Wangyong He Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China School of Engineering Tokyo University of Technology Tokyo Japan

Torque-ripples in a permanent magnet synchronous motor (PMSM) deteriorate control precision. This paper presents a method of attenuating such a kind of a torque-ripple based on the combination of the equivalent-input-disturbance (EID) and the sliding-mode control (SMC). While a low gain of an SMC system avoids chattering phenomenon, the robustness of the system is not satisfied. The EID estimator is incorporated in the system to solve this problem. The effectiveness of the combination of the EID approach and the SMC has been verified by simulations. A comparison with the conventional SMC method demonstrates the priority of the presented method.

关键词： Torque Sliding mode control Forging Harmonic analysis Synchronous motors Stators Attenuation

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Deep-Learning-based Identification of Influential Spreaders in Online Social Networks

Deep-Learning-based Identification of Influential Spreaders ...

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Annual Conference of the IEEE Industrial Electronics Society

作者： Feng Wang Jinhua She Yasuhiro Ohyama Min Wu School of Engineering Tokyo University of Technology Tokyo Japan Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China

Effective influential spreaders prediction in online social networks is critical for a variety of network services such as viral marketing, online recommendation, and many more. The conventional machine learning methods mainly adopted various hand-crafted features in the prediction models. However, their effectiveness relies on the domain knowledge heavily, and thus it is difficult to generalize these models to different domains. In this paper, we propose an Influence Deep Learning (IDL) model to learn users' latent feature representation for predicting influence spread. Our IDL model is fully data-driven, and it takes sampling subnetworks as input to the deep neural networks for learning users' latent vector representation. Moreover, we design a strategy to incorporate user-specific features and network structure into the graph convolutional neural network to overcome the imbalance problem of labeled training data. The experimental results show that our model outperforms other baselines in online social networks, and our model is more practical in large-scale data sets.

关键词： Social network services Machine learning Predictive models Neural networks Integrated circuit modeling Support vector machines Training

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Non-fragile finite-time dissipative piecewise control for time-varying system with time-varying delay

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IET control Theory & Applications 2019年第3期13卷 321-332页

作者： Menghua Chen Jian Sun School of Automation Beijing Institute of Technology Beijing 100081 People's Republic of China Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing 100081 People's Republic of China

This study is concerned with the problem of non-fragile finite-time dissipative (FTD) control for time-varying system with delay. The delay is time varying and belongs to a given interval. Finite-time bounded (FTB) and FTD concepts are introduced to time-varying system with delay. First, new FTB conditions are derived for time-varying system with delay by using a piecewise Lyapunov functional combined with reciprocally convex approach. Second, FTD conditions are obtained to guarantee that the time-varying system with delay is not only FTB but also satisfies a dissipative performance index. Moreover, based on the FTD conditions, the non-fragile piecewise feedback controllers are designed in terms of linear matrix inequalities (LMIs). In addition, an LMI-based iterative algorithm is given to obtain the piecewise feedback non-fragile controller gains. Finally, numerical examples demonstrate the effectiveness of the proposed method.

关键词： linear matrix inequalities delays feedback iterative methods control system synthesis Lyapunov methods time-varying systems performance index finite-time dissipative control time-varying system nonfragile piecewise feedback controllers piecewise feedback nonfragile controller gains time-varying delay nonfragile finite-time dissipative piecewise control finite-time bounded piecewise Lyapunov functional reciprocally convex approach dissipative performance index linear matrix inequalities LMI-based iterative algorithm

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Review on Development of Smart Education

Review on Development of Smart Education

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2019 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2019

作者： Shi, Wanruo Liu, Xiwei Gong, Xiaoyan Niu, Xiaojie Wang, Xinzhu Jing, Sifeng Lu, Hao Zhang, Nan Luo, Jie State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Faculty of Education Beijing Normal University Beijing China Institute of Smart Education Qingdao Academy of Intelligent Industries Qingdao China Chinese Association of Automation Beijing China State Key Laboratory of Software Development Environment Beihang University Beijing100191 China

ISBN: (纸本)9781728128535

Smart education is leading the development direction of Chinese education informatization and becoming a main theme of education development in the era of which technology changes education. There are seven main branches of smart education, namely intelligent Tutoring System (ITS), smart campus, Big Data in Education (BDE), knowledge graph, educational robots, virtual teachers, and personalized education. Based on literature survey and market research, this paper gives a comprehensive overview of the research and application of smart education from above seven aspects and proposes its development based on the status of smart education development. © 2019 IEEE.

关键词： intelligent vehicle highway systems

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