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Novel Cooperative Particle Swarm optimization with Interactive Learning Strategy 1

8th International Conference on Life System Modeling and Simulation, LSMS 2024 and 8th International Conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2024

作者： Wang, Qiliang Liu, Yiheng Xu, Hao Zhang, Pinggai Wu, Qinlin Wei, Lisheng Anhui Key Laboratory of Electric Drive and Control School of Electrical Engineering Anhui Polytechnic University Anhui Wuhu241000 China Industrial Process Control Optimization and Automation Engineering Research Center School of Electronic Engineering Chaohu University Anhui Chaohu238024 China School of Computer Science and Artificial Intelligence Chaohu University Anhui Chaohu238024 China

ISBN: (数字)9789819603138

ISBN: (纸本)9789819603121

Particle Swarm optimization (PSO) is an optimization method grounded in swarm intelligence, designed to mimic the social behaviors of bird flocks during hunting. By sharing information about their positions, the entire swarm can explore and search diverse areas within a given space. This method features rapid convergence, minimal parameters, and straightforward implementation, making it a potent and efficient metaheuristic technique. Nevertheless, conventional PSO algorithms, despite their simplicity and efficiency, often become trapped in local optima when tackling complex multimodal problems, which limits their global search capability. To mitigate these limitations, a new Cooperative Particle Swarm optimization algorithm with Interactive Learning (CPSOIL) is introduced. This approach incorporates an interactive learning strategy, allowing particles to learn from their neighbors by perceiving the surrounding particles during updates. Moreover, a mechanism has been added to modify the particle velocity update when the algorithm encounters local optima, thereby preserving population diversity, enhancing the likelihood of escaping local optima, and improving algorithm accuracy. Comparisons with other leading algorithms on the CEC2005 benchmark functions indicate that, in most cases, the enhanced algorithm outperforms its counterparts. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Particle swarm optimization (PSO)

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Data augmentation method for light guide plate based on improved CycleGAN

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Optoelectronics Letters 2024年

作者： GONG Yefei YAN Chao XIAO Ming LU Mingli GAO Hua School of Electrical and Automation Engineering，Changshu Institute of Technology Jiangsu Engineering Research Center of Industrial Robot Complex Process Intelligent Control School of Electrical Engineering， Yancheng Institute of Technology Wuxi Novo Automation Technology Corp

An improved CycleGAN network method for defect data augmentation based on feature fusion and self attention residual module is proposed to address the insufficiency of defect sample data for light guide plate(LGP) in production， as well as the problem of minor defects. Two optimizations are made to the generator of CycleGAN: 1) Fusion of low resolution features obtained from partial up-sampling and down-sampling with high-resolution features. 2) Combine self attention mechanism with residual network structure to replace the original residual module. Qualitative and quantitative experiments were conducted to compare different data augmentation methods， and the results showed that the defect images of the LGP generated by the improved network were more realistic， and the accuracy of the YOLOv5 detection network for the LGP was improved by 5.6%， proving the effectiveness and accuracy of the proposed method.

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Tracking performance limitations of MIMO discrete-time networked control systems with multiple constraints

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Science China(Information Sciences) 2023年第8期66卷 267-268页

作者： Xiaowei JIANG Bin ZHANG Xiangyong CHEN Huaicheng YAN School of Automation China University of Geosciences Key Laboratory of Industrial Internet of Things & Networked Control Ministry of Education Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education School of Automation and Electrical Engineering Linyi University Key Laboratory of Smart Manufacturing in Energy Chemical Process of the Ministry of Education

Dear editor,Networked control systems(NCSs) have attracted widespread attention in some fields because they offer the advantages of reduced cabling, greater resource sharing,and ease of installation and maintenance [1]. However, in an unreliable network environment, network constraints can significantly limit the performance of NCSs.

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Non-Monotonic Lyapunov-Krasovskii Functional Approach to Stability Analysis and Stabilization of Discrete Time-Delay Systems

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IEEE/CAA Journal of Automatica Sinica 2020年第3期7卷 752-763页

作者： Younes Solgi Alireza Fatehi Ala Shariati Advanced Process Automation and Control Research Group Industrial Control Center of ExcellenceFaculty of Electrical EngineeringK.N.Toosi University of TechnologyTehran 16317-14191Iran IEEE

In this paper, a novel non-monotonic Lyapunov-Krasovskii functional approach is proposed to deal with the stability analysis and stabilization problem of linear discrete time-delay systems. This technique is utilized to relax the monotonic requirement of the Lyapunov-Krasovskii theorem. In this regard, the Lyapunov-Krasovskii functional is allowed to increase in a few steps, while being forced to be overall decreasing. As a result, it relays on a larger class of Lyapunov-Krasovskii functionals to provide stability of a state-delay system. To this end, using the non-monotonic Lyapunov-Krasovskii theorem, new sufficient conditions are derived regarding linear matrix inequalities(LMIs)to study the global asymptotic stability of state-delay ***, new stabilization conditions are also proposed for time-delay systems in this article. Both simulation and experimental results on a p H neutralizing process are provided to demonstrate the efficacy of the proposed method.

关键词： Linear matrix inequality(LMI) non-monotonic Lyapunov-Krasovskii functional(NMLKF) pH neutralization plant stabilization state-delay system time-delay system

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DESIGN OF EUTROPHICATION MONITORING PLATFORM FOR CHAOHU CONNECTED RIVER CHANNEL BASED ON LoRa AND DEEP LEARNING

UPB Scientific Bulletin, Series C: Electrical Engineering an...

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UPB Scientific Bulletin, Series C: Electrical engineering and Computer Science 2023年第3期85卷 285-296页

作者： Kong, Bing Yu, Mei Ye, Song Xu, Xiaoyong Xiang, Rong School of Electronic Engineering Chaohu University Hefei Anhui China Graduate School Angeles University Foundation Manila Philippines School of Chemistry & Material Engineering Chaohu University Hefei Anhui China Industrial Process Control Optimization and Automation Engineering Research Center Chaohu University Hefei Anhui China Key Laboratory of Novel Ceramic and Powder Engineering Chaohu University Anhui China

Traditional methods cannot meet the requirements of real-time monitoring and scientific prevention and control of blue-green algae bloom. This paper uses multi-parameter sensors, LoRa module, 4G module, PLC and shore-based video acquisition device to build a monitoring platform to achieve real-time monitoring of multiple locations and real-time collection of video images;Aiming at the problem of image motion blur caused by shore-based video in water surface fluctuation, the Multi-scale Revolution Neural Network is used to effectively eliminate the visual artifacts of motion blur image, improve the monitoring accuracy of blue-green algae bloom, and meet the actual needs. © 2023, Politechnica University of Bucharest. All rights reserved.

关键词： Eutrophication

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Dynamic grouping of heterogeneous agents for exploration and strike missions

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Frontiers of Information Technology & Electronic engineering 2022年第1期23卷 86-100页

作者： Chen CHEN Xiaochen WU Jie CHEN Panos M.PARDALOS Shuxin DING School of Automation Beijing Institute of TechnologyBeijing100081China Department of Control Science and Engineering Tongji UniversityShanghai200092China Center for Applied Optimization Department of Industrial and Systems EngineeringUniversity of FloridaGainesvilleFL32611USA Signal and Communication Research Institute China Academy of Railway Sciences Corporation LimitedBeijing100081China

The ever-changing environment and complex combat missions create new demands for the formation of mission groups of unmanned combat *** study aims to address the problem of dynamic construction of mission groups under new *** are heterogeneous,and a group formation method must dynamically form new groups in circumstances where missions are constantly being *** our method,a group formation strategy that combines heuristic rules and response threshold models is proposed to dynamically adjust the members of the mission group and adapt to the needs of new *** degree of matching between the mission requirements and the group’s capabilities,and the communication cost of group formation are used as indicators to evaluate the quality of the *** response threshold method and the ant colony algorithm are selected as the comparison algorithms in the *** results show that the grouping scheme obtained by the proposed method is superior to those of the comparison methods.

关键词： Multi-agent Dynamic missions Group formation Heuristic rule Networking overhead

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Adaptive Pseudo Inverse control for a Class of Nonlinear Asymmetric and Saturated Nonlinear Hysteretic Systems

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IEEE/CAA Journal of Automatica Sinica 2021年第4期8卷 916-928页

作者： Xiuyu Zhang Ruijing Jing Zhiwei Li Zhi Li Xinkai Chen Chun-Yi Su School of Automation Engineering Northeast Electric Power Universityand also with Jilin Province International Research Center of Precision Drive and Intelligent ControlJilin 132012China State Key Laboratory of Synthetical Automation for Process Industries Northeastern UniversityShenyang 110819China Department of Electronic and Information Systems Shibaura Institute of TechnologySaitama 337-8570Japan Department of Mechanical and Industrial Engineering Concordia UniversityQCMontreal H3B 1R6Canada

This paper aims at eliminating the asymmetric and saturated hysteresis nonlinearities by designing hysteresis pseudo inverse compensator and robust adaptive dynamic surface control(DSC)***"pseudo inverse"means that an on-line calculation mechanism of approximate control signal is developed by applying a searching method to the designed temporary control signal where the true control signal is *** main contributions are summarized as:1)to our best knowledge,it is the first time to compensate the asymmetric and saturated hysteresis by using hysteresis pseudo inverse compensator because the construction of the true saturated-type hysteresis inverse model is very difficult;2)by designing the saturated-type hysteresis pseudo inverse compensator,the construction of true explicit hysteresis inverse and the identifications of its corresponding unknown parameters are not required when dealing with the saturated-type hysteresis;3)by combining DSC technique with the tracking error transformed function,the"explosion of complexity"problem in backstepping method is overcome and the prespecified tracking performance is *** of stability and experimental results on the hardware-inloop platform illustrate the effectiveness of the proposed adaptive pseudo inverse control scheme.

关键词： Adaptive dynamic surface control adaptive pseudo inverse control asymmetric and saturated hysteresis robust control

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Two Feature Fusion Network Based on Efficient Deep Residual Shrinkage Spatial-Temporal Graph Convolution for Emotion Recognition from Gaits

Two Feature Fusion Network Based on Efficient Deep Residual ...

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第34届中国控制与决策会议

作者： Xiaoqing Liu Sen Zhang Wendong Xiao School of Automation and Electrical Engineering University of Science and Technology Beijing Key Laboratory of Advanced Control of Iron and Steel Process (Ministry of Education) Shunde Graduate School University of Science and Technology Beijing Beijing Engineering Research Center of Industrial Spectrum Imaging

Emotion Recognition plays a key role in human social *** current methods choose facial information for emotion *** facial information is easily limited by distance in large *** information can break this limitation,but the amount of publicly available data is *** paper proposes two feature fusion network based on efficient deep residual shrinkage spatial-temporal graph convolution to achieve automatic emotion recognition from gaits in large *** chebyshev polynomial approximation graph convolution is combined with efficient deep residual shrinkage network to obtain efficient deep residual shrinkage spatial-temporal graph convolution network to extract deep *** sixteen temporal affective features extracted from gaits are used as input of efficient deep residual shrinkage network to extract new affective *** the deep features is spliced with new affective features to divided emotion into happy,angry,sad and *** performed a ten-flod cross-validation experiment on the E-gait real *** highest recognition accuracy is 0.87,with an average of *** results show that the proposed model is effective in dealing with emotion recognition promblem from gait in fewer sample situation.

关键词： emotion recognition from gaits chebyshev polynomial approximation deep residual shrinkage Network efficient channel attention mechanism

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Two Feature Fusion Network Based on Efficient Deep Residual Shrinkage Spatial-Temporal Graph Convolution for Emotion Recognition from Gaits

Two Feature Fusion Network Based on Efficient Deep Residual ...

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Chinese control and Decision Conference, CCDC

作者： Xiaoqing Liu Sen Zhang Wendong Xiao School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing China Key Laboratory of Advanced Control of Iron and Steel Process (Ministry of Education) Beijing China Shunde Graduate School University of Science and Technology Beijing Foshan China Beijing Engineering Research Center of Industrial Spectrum Imaging Beijing China

ISBN: (纸本)9781665478977

Emotion Recognition plays a key role in human social activities. Most current methods choose facial information for emotion recognition. But facial information is easily limited by distance in large scenes. Gait information can break this limitation, but the amount of publicly available data is small. This paper proposes two feature fusion network based on efficient deep residual shrinkage spatial-temporal graph convolution to achieve automatic emotion recognition from gaits in large scenes. Firstly chebyshev polynomial approximation graph convolution is combined with efficient deep residual shrinkage network to obtain efficient deep residual shrinkage spatial-temporal graph convolution network to extract deep features. Then sixteen temporal affective features extracted from gaits are used as input of efficient deep residual shrinkage network to extract new affective features. Finally the deep features is spliced with new affective features to divided emotion into happy,angry,sad and neutral. We performed a ten-flod cross-validation experiment on the E-gait real datasets. The highest recognition accuracy is 0.87, with an average of 0.85. Experimental results show that the proposed model is effective in dealing with emotion recognition promblem from gait in fewer sample situation.

关键词： Emotion recognition Convolution Chebyshev approximation Feature extraction

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Room Impulse Response Reshaping-Based Blind Source Separation for an Underdetermined Reverberant Environment

SSRN

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SSRN 2024年

作者： Xie, Yuan Zou, Tao Yang, Junjie Sun, Weijun Xie, Shengli School of Mechanical and Electrical Engineering Guangzhou University Guangdong-Hong Kong-Macao Key Laboratory of Multi-scale Information Fusion and Collaborative Optimization Control of Complex Manufacturing Process Guangzhou510006 China School of Automation Guangdong University of Technology Joint International Research Laboratory of Intelligent Information Processing and System Integration of IoT Ministry of Education of the P.R.C. Guangzhou510006 China School of Automation Guangdong University of Technology Guangdong Key Laboratory of IoT Information Processing Guangdong-HongKong-Macao Joint Laboratory for Smart Discrete Manufacturing Guangzhou510006 China School of Automation Guangdong University of Technology Key Laboratory of Intelligent Detection and the IoT in Manufacturing Ministry of Education 111 Center for Intelligent Batch Manufacturing Based on IoT Technology Guangzhou510006 China

Blind source separation under an underdetermined reverberation environment is a very challenging issue. The classical method is based on the expectation maximization algorithm. However, it is limited to high reverberation environments, resulting in bad or even invalid separation performance. To eliminate this restriction, a room impulse response reshaping-based expectation maximization method is designed to solve the problem of blind signal separation in an underdetermined reverberant environment. Firstly, a room impulse response reshaping technology is designed to eliminate the influence of audible echo on the reverberant environment, improving the quality of the received signals. Then, a new mathematical model of time-frequency mixing signals is established to reduce the approximation error of model transformation caused by high reverberation. Furthermore, an improved expectation maximization method is proposed for real-time update learning rules of model parameters, and then the sources are separated using the estimators provided by the improved expectation maximization method. Experimental results based on source separation of speech and music mixtures demonstrate that the proposed algorithm achieves better separation performance while maintaining much better robustness than popular expectation maximization methods. © 2024, The Authors. All rights reserved.

关键词： Reverberation

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