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2021 China automation Congress, CAC 2021

作者： Liu, Bo-Wen Xu, Da He, Yong School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9781665426473

The global coronavirus disease (COVID-19) has brought great challenges to the power systems due to its limitations on social, economic and productive activities. This paper proposes a short-term load forecasting method during COVID-19 pandemic based on copula theory and eXtreme Gradient Boosting (XGBoost). In this method, the coupling relationship among the cross-domain meteorological, public health, and mobility time-series data are fully analyzed based on copula theory, which is used for the short-term power load forecasting based on multi-factor fusion XGBoost algorithm. The proposed method has been fully evaluated and benchmarked on available cross-domain open-access United States data to demonstrate its effectiveness and superiority on short-term load forecasting of COVID-19. © 2021 IEEE

关键词： COVID-19

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Stability and Bifurcation control of Fractional BAM Neural Networks with Diffusion and Time Delays

Stability and Bifurcation control of Fractional BAM Neural N...

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第42届中国控制会议

作者： Feng Liu Wei Wang Gang Cai Feifan Zhou Hua O Wang Xiuqin Yang School of Automation China University of Geosciences Engineering Research Center of Ministry of education for intelligent technology of earth exploration Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Department of Mechanical Engineering Boston University

Based on fractional calculus theory and reaction-diffusion equation theory,a fractional-order time-delay reaction-diffusion neural network with Neumann boundary conditions is *** constructing the phase space basis based on the Laplace operator eigenvector,the system equation is linearized to obtain the characteristic ***,the characteristic equation is analyzed,and the local stability of the system at the equilibrium point is *** taking the time delay as the bifurcation parameter,the stability changes of the system at the equilibrium point and the generation conditions of the Hopf bifurcation are studied when the time delay ***,a state feedback controller is designed to control the bifurcation of the ***,the theoretical derivation is verified by numerical simulation.

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Dynamic analysis and control of fractional order memristor Hopfield neural network

Dynamic analysis and control of fractional order memristor H...

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第42届中国控制会议

作者： Feng Liu Gang Cai Feifan Zhou Wei Wang Hua Wang Xiuqin Yang School of Automation China University of Geosciences Engineering Research Center of Ministry of education for intelligent technology of earth exploration Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Department of Mechanical Engineering Boston University

In this paper, a novel smooth magnetron is introduced to construct a fractional memristor Hopfield neural network(fractional order M-HNN). The local stability of equilibrium point are analyzed theoretically. Taking the memristor coupling strength coefficient and the fractional order as bifurcation parameters, the phase trajectory diagram, the bifurcation diagram of the system are drawn to analyze the influence on the dynamic behavior of the neural network. When the system parameters are fixed, the hyperchaos phenomenon of the fractional order M-HNN model is revealed. Finally, the PD controller is applied to the model to enhance the stability of the system.

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Automatic Target Recognition in GPR Images Based on Time-Frequency Texture Features and Support Vector Machine

Automatic Target Recognition in GPR Images Based on Time-Fre...

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2021 China automation Congress, CAC 2021

作者： Chen, Kehui Xue, Wei Wang, Zexi Ma, Shaopeng School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9781665426473

Ground penetrating radar (GPR) images are easily disturbed by noise, which causes a lot of difficulties for target recognition. To improve the target recognition performance in GPR images, a novel recognition method based on time-frequency texture features and support vector machine (SVM) is proposed. The proposed method first extracts texture features from the gray co-occurrence matrix of S transform time-frequency images for the A-scan data, then establishes the SVM model and realizes the target recognition. The proposed method is assessed using synthetic GPR images and compared with other two time-frequency analysis methods, combined with SVM. The expermental results show that the proposed method can achieve higher recognition accuracies than the other two methods in heavily noisy environment. © 2021 IEEE

关键词： Support vector machines

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Coverage control of Unmanned Aerial Vehicles for Periodical Monitoring of Geohazards

Coverage Control of Unmanned Aerial Vehicles for Periodical ...

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2021 IEEE International Conference on Unmanned systems, ICUS 2021

作者： Zhang, Wei Zhai, Chao School of Automation China University of Geosciences Research Center of Intelligent Technology for Geo-Exploration Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Ministry of Education Wuhan430074 China

ISBN: (纸本)9780738146577

Landslides have become one of the major hazards endangering the lives and property of people all over the world. In order to improve the early warning of geohazards, a cooperative coverage control algorithm of unmanned aerial vehicles (UAV) is developed in this paper. The proposed control algorithm is integrated with the airborne radar to periodically monitor the surface deformation, which is closely related to the emergence of geohazards. A Lyapunov function is constructed to ensure the stability of UAVs driven by the proposed control algorithm. Numerical simulations are conducted to substantiate the coverage control approach for UAVs in the uncertain environment. This work provides new insight into the effective monitoring and early warning of geohazards with the assistance of UAVs. © 2021 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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A Subspace-Based Non-Dominated Subset Selection Method

A Subspace-Based Non-Dominated Subset Selection Method

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2023 IEEE Congress on Evolutionary Computation, CEC 2023

作者： Tan, Qingshan Li, Changhe Zeng, Sanyou Yang, Shengxiang Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China School of Mechanical Engineering and Electronic Information China University of Geosciences Wuhan430074 China School of Computer Science and Informatics De Montfort University LeicesterLE1 9BH United Kingdom

ISBN: (纸本)9798350314588

Environmental selection is an important process in multi-objective evolutionary algorithms (MOEAs). As the evolution progresses, the number of non-dominated solutions increases. This paper is focused on selecting a subset from excess non-dominated solutions for evolutionary or the final output. However, traditional selection methods in classical MOEAs encounter difficulties when dealing with candidate solutions that possess irregular topologies. Although the distance-based subset selection methods are not sensitive to the topologies of the candidate points, they have significant room for reducing computational complexity. In order to address the above issues, a subspace selection method is proposed in this paper. It partitions the objective space into multiple subspaces that have comparable volumes and shapes. The maximal minimum distance of each solution is considered to ensure that the sparsest solution is always chosen first. To save computational costs, only the solutions in the neighboring subspaces are taken into account. The experimental results demonstrate that the proposed subspace selection method outperforms classical selection methods in solving problems with various shapes of the Pareto front. © 2023 IEEE.

关键词： Multiobjective optimization

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Oscillation Trajectory Optimization and control Method for Two-link Underactuated Manipulators

Oscillation Trajectory Optimization and Control Method for T...

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第42届中国控制会议

作者： Lejun Wang Huiming Wang Xianlun Tang Zixin Huang Chongqing Key Laboratory of Complex Systems and Bionic Control Chongqing University of Posts and Telecommunications Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Hubei Key Laboratory of Digital Textile Equipment Wuhan Textile University School of Electrical and Information Engineering Wuhan Institute of Technology

This paper provides an oscillation trajectory optimization and control method for two-link underactuated manipulators(UMs) in a vertical *** proposed method solves the problem that the UMs cannot always enter the balance region in the partitioning ***,we establish the system dynamic model,and analyze the system couple ***,we program an oscillation trajectory for the active link,and use the intelligent method to obtain the trajectory parameters,so ensuring the system can reach the area adjacent to the target position through tracking ***,we design the controller to realize the stable control at the target ***,the simulation results show the effectiveness and generality of the control strategy.

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EMOST: A dual-branch hybrid network for medical image fusion via efficient model module and sparse transformer

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Computers in Biology and Medicine 2024年 179卷 108771-108771页

作者： Wang, Wenqing He, Ji Liu, Han School of Automation and Information Engineering Xi'an University of Technology Xi'an710048 China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an710048 China

Multimodal medical image fusion fuses images with different modalities and provides more comprehensive and integrated diagnostic information. However, current multimodal image fusion methods cannot effectively model non-local contextual feature relationships, and due to direct aggregation of the extracted features, they introduce unnecessary implicit noise into the fused images. To solve the above problems, this paper proposes a novel dual-branch hybrid fusion network called EMOST for medical image fusion that combines a convolutional neural network (CNN) and a transformer. First, to extract more comprehensive feature information, an effective feature extraction module is proposed, which consists of an efficient dense block (EDB), an attention module (AM), a multiscale convolution block (MCB), and three sparse transformer blocks (STB). Meanwhile, a lightweight efficient model (EMO) is used in the feature extraction module to exploit the efficiency of the CNN with the dynamic modeling capability of the transformer. Additionally, the STB is incorporated to adaptively maintain the most useful self-attention values and remove as much redundant noise as possible by developing the top-k selection operator. Moreover, a novel feature fusion rule is designed to efficiently integrate the features. Experiments are conducted on four types of multimodal medical images. The proposed method shows higher performance than the art-of-the-state methods in terms of quantitative and qualitative evaluations. The code of the proposed method is available at https://***/XUTauto/EMOST. © 2024 Elsevier Ltd

关键词： Feature extraction

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A 3D Point Attacker for LiDAR-Based Localization

A 3D Point Attacker for LiDAR-Based Localization

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International Conference on control and automation (ICCA)

作者： Shiquan Yi Jiakai Gao Yang Lyu Lin Hua Xinkai Liang Quan Pan School of Automation Northwestern Polytechnical University Xi'an Shaanxi PR China National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Beijing PR China

ISBN: (数字)9798350354409

ISBN: (纸本)9798350354416

The safety and security issues of autonomous navigation function become the main obstacles that hinder the widespread applications of self-driving cars and unmanned systems. In this paper, we investigate the vulnerability of LiDAR-based localization methods to adversarial attacks. Specifically, we developed a feature-based spoofing attack strategy to degrade the localization performance of LiDAR-based localization algorithms. Reflecting on the vulnerability, we additionally provide a resilient strategy to defend existing LiDAR-based localization methods against this attack. The proposed attack strategy is tested on the KITTI dataset to illustrate its effectiveness.

关键词： Location awareness Simultaneous localization and mapping Laser radar Accuracy Three-dimensional displays Perturbation methods Feature extraction

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Formulation of Optimization Problems with Radiation Field Phases as Design Variables for Pattern Synthesis of Linear Antenna Arrays

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China Communications 2022年第12期19卷 86-100页

作者： Fei Zhao Jun He Sanyou Zeng Changhe Li Qinghui Xu Zhigao Zeng School of Mechanical Engineering and Electronic Information China University of GeosciencesWuhan 430074China Science and Technology on Blind Signal Processing Laboratory Southwest Electronics and Telecommunication Technology Research InstituteChengdu 610041China School of Automation China University of GeosciencesWuhan 430074China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan 430074China College of Computer Hunan University of TechnologyZhuzhou CityHunan Province412007China

Pattern synthesise of antenna arrays is usually complicated optimization problems,while evolutionary algorithms(EAs)are promising in solving these *** paper does not propose a new EA,but does construct a new form of optimization *** new optimization formulation has two differences from the common *** is the objective function is the field error between the desired and the designed,not the usual amplitude error between the desired and the *** difference is beneficial to decrease complexity in some *** second difference is that the design variables are changed as phases of desired radiation field within shaped-region,instead of excitation *** difference leads to the reduction of the number of design variables.A series of synthesis experiments including equally and unequally spaced linear arrays with different pattern shape requirements are applied,and the effectiveness and advantages of the proposed new optimization problems are *** results show that the proposing a new optimization formulation with less complexity is as significant as proposing a new algorithm.

关键词： pattern synthesis evolutionary algorithms linear antenna arrays

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