检索结果-内蒙古大学图书馆

第32届中国过程控制会议(CPCC2021)

作者： Sha He Jing Wu Shaoyuan Li Dan Huang Dongqi Lu Department of Automation and Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University Taizhou Power Supply Company of State Grid Zhejiang Electric Power Co. Ltd

As the most successful oversampling algorithm,the SMOTE algorithm and its numerous extensions are widely used for imbalanced problem,which is long-standing and challenging for classification ***,the performance of these methods is greatly affected by the data distribution due to the use of local *** this paper,we propose a novel oversampling technique based on global distribution to deal with imbalance *** calculating the classification error,a contribution factor is assigned to each sample with a sampling weight,which can synthesize samples contribute and accurate the classification ***,the dynamic attention is also introduced to help synthetic samples to balance efficiency and *** changes the space we pay attention to by an attention factor as the sample synthesis *** conduct experiments on different data sets and compare our method with other existing over-sampling techniques,which demonstrates that our approach can realize better classification performance.

关键词： oversampling technique imbalanced problem classification dynamic attention

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Obstacle Avoidance Algorithm Based on Human Experience Knowledge

Obstacle Avoidance Algorithm Based on Human Experience Knowl...

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IEEE Conference on Vehicular Technology (VTC)

作者： Hao Jiang Yushan Li Xuda Ding Jianping He Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9781728194844

ISBN: (纸本)9781728194851

This paper studies the obstacle avoidance problem of mobile vehicles. Most of the existing algorithms for obstacle avoidance are proposed for specific environments, lacking adaptability for various environments. Motivated by mimicking the obstacle-avoidance actions of humans in different environments, this paper proposes a human experience knowledge (HEK) based obstacle avoidance algorithm. The proposed algorithm provides reliable support for mobile vehicles to implement tasks in a complex environment. Specifically, we first characterize the related experience knowledge of humans by converting to categorical variables. Then, a logistic regression method is utilized to model the corresponding knowledge based on categorical variables. Finally, the HEK-based algorithm, which dynamically adapts to different situations, is designed according to the corresponding knowledge model. Extensive comparative simulation results are conducted to demonstrate that the proposed algorithm has better adaptability and flexibility for various static obstacle environments and a low computational cost.

关键词： Adaptation models Vehicular and wireless technologies Heuristic algorithms Simulation Computational modeling Turning Collision avoidance

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Explorative Policy Optimization for industrial-scale operation of complex process control systems

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Journal of Process control 2025年 152卷

作者： Zengjun Zhang Shaoyuan Li Yaru Yang Department of Automation Shanghai Jiao Tong University Shanghai 200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Jiao Tong University Shanghai 200240 China

With the advancement of industrial automation, traditional process control methods increasingly struggle to manage the complex operational demands of industrial-scale chemical processes, particularly in the presence of unmodelled dynamics and high nonlinearity. This paper introduces an advanced reinforcement learning algorithm, Explorative Policy Optimization (EPO), specifically developed to optimize operational strategies, focusing on improving both production yield and product quality in such environments. The core innovation of the EPO algorithm is its exploration network, which dynamically adjusts exploration strategies based on discrepancies between predicted and actual values of state–action pairs, enabling more effective exploration. This approach improves decision-making by providing more accurate outcome assessments in complex and unmodelled conditions. EPO also integrates exploration data into the advantage function, ensuring a balance between exploration and exploitation, which is essential for optimizing performance in dynamic environments that require both safety and adaptability. EPO focuses on global optimization in processes with multiple operating conditions and steady states. It surpasses existing RL methods in overall performance while maintaining acceptable computational costs across a wide range of industrial settings. Its effectiveness and practicality are demonstrated through industrial-scale simulation experiments.

关键词： Explorative policy Industrial optimization Process control Reinforcement learning

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fMRI-based Brain Disease Diagnosis: A Graph Network Approach

TechRxiv

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TechRxiv 2023年

作者： Chen, Qi-Qi Gao, Yubing Tong, Wei Li, Ping Wu, Edmond Q. The Department of Automation Shanghai Jiao Tong University Shanghai200240 China The Nanjing University of Science and Technology Jiangsu210008 China The School of Biological Science and Medical Engineering Beihang University Beijing100191 China The Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Jiao Tong University Shanghai200240 China The Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai200240 China

As a non-invasive brain imaging technology, functional magnetic resonance imaging (fMRI) provides a basic tool for brain functional network modeling and brain disease diagnosis. Problems, such as large number of parameters, low training efficiency, and poor interpretability, are encountered in mainstream models because of the high complexity of fMRI and brain networks. To solve these problems, a novel structure feature combined graph neural network (SFC-GNN) with a low number of parameters is proposed. In particular, SFC-GNN is composed of 1) the graph convolution layer of the brain region perception and 2) the node pooling layer of the graph structure feature (GSF). It also receives the sparse brain graph modeled by each subject’s fMRI as input. Especially, the GSF layer can select brain regions that are important for classification, thereby localizing all active regions related to brain disease. Moreover, a group network is constructed according to the correlation among subjects, and SFC-GNN can be extended further to a node classification model to achieve better diagnosis performance. The proposed method has been validated on the ABIDE and ADNI datasets, thereby showing the effectiveness of our proposed method in various experiments. © 2023, CC BY.

关键词： Magnetic resonance imaging

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An edge-based model for non-Markovian sexually transmitted infections in coupled network

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International Journal of Biomathematics 2020年第2期13卷 119-153页

作者： Xiaofeng Luo Junyuan Yang Zhen Jin School of Computer and Information Technology Shanxi University Taiyuan 030006P.R.China Complex System Research Center Shanxi University Taiyuan 030006ShanxiP.R.China Shanxi Key Laboratory of Mathematical Techniques and Big DataAnalysis on Disease Control and Prevention Shanxi University Taiyuan 030006ShanxiP.R.China Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education Taiyuan 030006 P.R.China

In this paper,allowing for general transmission and recovery times distributions,we proposed an edge-based age-structured-like compartmental model for STIs(EBACMS)in a coupled *** considered sexual transmissions between men with also heterosexual ***,we gave the general approach of proving the nonnegativity of solutions for the system coupling ordinary and partial differen-tial equations,which can be applied to all edge-based compartment *** then analyzed the epidemic threshold Ro with different distributions which couples the thresholds of the single-layer and bipartite networks in the percolation *** also studied the global stability of disease-free equilibrium with R0<1 and the final epidemic size F(the proportion of the population experiencing infection during the epidemic)with R0>*** addition,numerical simulations indicated that given a fixed exponential transmission distribution,a higher variance(with same mean)in general recovery distribution gives smaller R0 and *** analysis on Ro and F in terms of the parameters illustrated that male-to-male transmission routes have a greater impact on Rg and F than the heterosexual transmission routes for the Markovian transmission process and arbitrary recovery *** results provide a good theoretical guideline to consider the distributions of real-world STIs.

关键词： Coupled network EBCM non-Markovian process sexually transmitted disease epidemic age-structured

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Point Cloud Preprocessing on 3D LiDAR data for Unmanned Surface Vehicle in Marine Environment

Point Cloud Preprocessing on 3D LiDAR data for Unmanned Surf...

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2020 IEEE International Conference on information Technology, Big Data and Artificial Intelligence, ICIBA 2020

作者： Qi, Xianzhi Fu, Wenxing An, Pei Wu, Bingli Ma, Jie National Key Laboratory of Science and Technology on Multispectral Information Processing School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100071 China

ISBN: (纸本)9781728152240

Point cloud preprocessing is still a challenging task in the marine environment, for it is difficult to filter out non-obstacle points while avoiding damage to the obstacle completeness. In this paper, we propose a novel data preprocessing method on 3D LiDAR data for the unmanned surface vehicle in the marine environment. It consists of two tasks: outlier removal and wake filtering. As the spatial resolution of LiDAR changes with distance, we exploit distance normalization on statistical outlier filter for robust outlier removal. Considering the gradient difference between wave wake and obstacle surface near the water, we define and calculate the vertical state of point cloud on the range image to obtain the pre-filtering point set, and then use the RANSAC method to filter out the wake points. Experiments on real data has demonstrated the effectiveness of the proposed algorithm both in terms of feasibility and accuracy. © 2020 IEEE.

关键词： Wakes

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Obstacle Avoidance-based control system Design of UAV with Suspended Payload

Obstacle Avoidance-based Control System Design of UAV with S...

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第三十九届中国控制会议

作者： Zhiheng Ren Chaofang Hu Hao Wu Binghan Sun Yao Guo School of Electrical and Information Engineering Tianjin University Key Laboratory of System Control and Information Processing Ministry of Education

In this paper, the flight safety of quadrotor UAV with suspended payload in presence of obstacle is addressed. The trajectory planning and stability control are discussed to minimize the payload swing. Firstly, a comprehensive model of quadrotor UAV with payload system is established. Then, for given waypoints, Cubic curve is used to generate a feasible reference trajectory in urban environment. In suburban, Dubins trajectory method is introduced to generate smooth and continuous obstacle avoidance trajectory. Predictive control is used to find the shortest route with minimizing payload swing by avoiding unknown obstacles in real-time. The hierarchical control structure of inner-loop attitude and outer-loop position using PID is adopted in the design of trajectory tracking. The simulation results verify the feasibility of obstacle avoidance strategy for UAV flying with a suspended payload.

关键词： UAV Obstacle avoidance Payload Trajectory planning Dubins

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Deep Hashing Network Based on Split Channels for Hybrid-Source Remote Sensing Image Retrieval

Deep Hashing Network Based on Split Channels for Hybrid-Sour...

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2020年第三届国际人工智能和模式识别会议

作者： Salayidin Sirajidin Hong Huo Tao Fang Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing

Traditional remote sensing image retrieval(RSIR) methods are generally based on images from a specific single source. As different sources and huge volumes of remote sensing images have been easily available nowadays, RSIR is facing the challenge of retrieving remote sensing images with different spectral and spatial information from different sources. Benefited from compelling image feature extraction ability of deep neural networks and efficient computing power and effective retrieval ability of hashing, deep hashing networks has become prevalent for image retrieval researches. In this paper, a deep hashing network based on split channels is proposed for hybrid source RSIRcalledsplit-channelstripletdeephashing networks(SCTDHNs). It takes skillfully splitting channels as input,and is mainly composed of a hybrid source deep hashing subnetwork for cross source images retrieval and single-source deep hashing sub-network for a multi-spectral image retrieval, and each of them achieves high retrieval performance. Furthermore, a novel trick for loss function is proposed, called increased intervals between dissimilar pairs during training stage that dramatically improves theretrieval *** experiments implement on dual-source remote sensing data set demonstrate that proposed method yields better performance than existing state-of-art hybrid source retrieval methods as far as is known.

关键词： Split-channels deep hashing network dual-source remote sensing data set supervised hashing

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Smart Energy Dispatch for Networked Microgrids systems Based on Distributed control Within a Hierarchy Optimization

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IFAC-PapersOnLine 2020年第2期53卷 12999-13004页

作者： Ibrahim Brahmia Jingcheng Wang Yuanhao Shi Yang Lan Dept. of Automation Shanghai Jiaotong University and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240

Cooperative microgrids considered the next generation of smart energy trading technology. A promising solution is proposed in this paper, for smart energy management of cooperative multi microgrids (MMGs) systems based on dual level distributed strategy, achieved by two layers model predictive control (MPC) for optimal operation and energy scheduling of the DERs, and energy trading among multi-microgrids system, with efficient economic cost reduction. We employed a distributed system operator (DSO) as a supervisory layer for energy trading and dynamic power balance ensuring. Along with the local controller as a lower layer for tracking a reference trajectory from the upper layer, we developed an online algorithm with a hierarchical structure to solve the energy dispatching problem within dual-level optimization, offering an environmental-friendly control solution, due to reduction of fuel consumption. Finally, simulation results are presented to witness the advantages of our distributed algorithm approach in comparison to a noncooperative strategy.

关键词： Microgrids MPC Smart grid energy management Dual-level optimization

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Partial observer canonical form for multi-output nonlinear forced system: a new method

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Journal of Intelligent Manufacturing and Special Equipment 2020年第1期1卷 121-134页

作者： Haotian Xu Jingcheng Wang Hongyuan Wang Ibrahim Brahmia Shangwei Zhao Key Laboratory of System Control and Information Processing Department of Automation Ministry of Education of China Shanghai Jiao Tong University Shanghai China

Purpose The purpose of this paper is to investigate the design method of partial observer canonical form (POCF), which is one of the important research tools for industrial plants. Design/methodology/approach Motivated by the two-steps method proposed in Xu et al. (2020), this paper extends this method to the case of Multi-Input Multi-Output (MIMO) nonlinear system. It decomposes the original system into two subsystems by observable decomposition theorem first and then transforms the observable subsystem into OCF. Furthermore, the necessary and sufficient conditions for the existing of POCF are proved. Findings The proposed method has a wide range of applications including completely observable nonlinear system, noncompletely observable nonlinear system, autonomous nonlinear system and forced nonlinear system. Besides, comparing to the existing results (Saadi et al., 2016), the method requires less verified conditions. Originality/value The new method concerning design POCF has better plants compatibility and less validation conditions.

关键词： Multi-output nonlinear system Partial observer canonical form Two-step method Nonlinear observable decomposition

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