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2nd International Conference of Mechanical system Dynamics, ICMSD 2023

作者： Wang, Pingxin Zhang, Jianshu Rui, Xiaoting Wang, Guoping Wang, Xun Nanjing University of Science and Technology Nanjing China National Key Laboratory of Complex Multibody System Dynamics Nanjing China

ISBN: (纸本)9789819980475

Tracked vehicles are extensively used in both industry and agriculture, and the vibration they generate has a significant effect on occupant comfort. In order to reduce this vibration, it is essential to study the vibration characteristics of the system. Utilizing the Transfer Matrix Method for Multibody systems (MSTMM), a dynamic model of a tracked vehicle was established which was composed of the barrel, pitch body, revolved body, chassis, sprockets, idlers, support rollers, road wheels, road arms, track links and track pins. The track link was modelled as a spatial rigid body and the connections between tracks and wheels as well as the ground were modelled as elastic hinges. A calculation algorithm for vibration characteristics was then developed by solving the overall transfer equation. The proposed dynamic model and the selected parameters were verified through a modal test, thus providing a foundation for evaluating the dynamic performance of tracked vehicle systems. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Tracked vehicles

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Convolution Neural Network-based Load Model Parameter Selection Considering Short-term Voltage Stability

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CSEE Journal of Power and Energy systems 2024年第3期10卷 1064-1074页

作者： Ying Wang Chao Lu Xinran Zhang School of Technology Beijing Forestry UniversityBeijing 100083China State Key Laboratory of Control and Simulation of Power System and Generation Equipment Tsinghua UniversityBeijing 100084China School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100083China IEEE

The recently proposed ambient signal-based load modeling approach offers an important and effective idea to study the time-varying and distributed characteristics of power ***,it also brings new *** the load model parameters of power loads can be obtained in real-time for each load bus,the numerous identified parameters make parameter application *** order to obtain the parameters suitable for off-line applications,load model parameter selection(LMPS)is first introduced in this ***,the convolution neural network(CNN)is adopted to achieve the selection purpose from the perspective of short-term voltage *** begin with,the field phasor measurement unit(PMU)data from China Southern Power Grid are obtained for load model parameter identification,and the identification results of different substations during different times indicate the necessity of ***,the simulation case of Guangdong Power Grid shows the process of LMPS,and the results from the CNNbased LMPS confirm its effectiveness.

关键词： Ambient signal CNN field PMU data load model parameter selection short-term voltage stability

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Compression Format and Systolic Array Structure Co-design for Accelerating Sparse Matrix Multiplication in DNNs 24th

Compression Format and Systolic Array Structure Co-design f...

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24th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2024

作者： Cao, Yongxiang Jiang, Jixiang Zhao, Guocheng Wang, Wei Jiang, Hongxu Song, Yanfei School of Computer Science and Engineering Beihang University Beijing China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (纸本)9789819615445

The systolic array (SA) architecture is widely used in accelerator/AI chip design due to its excellent matrix multiplication acceleration effect. However, the mismatch between the traditional sparse matrix compression format and the SA architecture results in poor SA performance in computing sparse matrices. To solve the problem, we propose a method for co-designing the sparse compression format and SA architecture. This work proposes the Vector Group Compressed Coordinate (VGCC) data stream compression format and designs a sparse SA architecture based on hardware encoding and decoding. VGCC can handle data streams of any size without increasing the index bit width. The VGCC compression size is significantly smaller than general sparse compression formats such as COO/CSR. In a sparse matrix with a sparsity of 90%, it saves 67.13% of storage space compared to the state-of-the-art ECOO data stream compression format and achieves an average acceleration of 1.54 times. We also propose a VGCC-friendly SA architecture. Our SA architecture engine reduces logic consumption by 51.6% compared to Sparse TPU while achieving a 3.23x speedup. To mitigate the issue of high no-load rates in systolic arrays, we introduce a Data Transmission Priority (DTP) data matching algorithm. With sparsity levels ranging from 50% to 90%, the algorithm’s calculation speed is enhanced by 1.124x to 1.991x. We implemented a sparse DNN accelerator on an FPGA Zynq UltraScale+MPSoC ZCU102, utilizing the VGCC compression format proposed in this study for compressing input data. When compared to the S2 Engine, the accelerator achieved a 3.37x speed improvement in matrix multiplication with 75% sparsity, significantly enhancing the speed of sparse matrix multiplication. The accelerator achieved an average throughput of 1079.33GOP/s when inferencing DNNs. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Systolic arrays

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EPM-Net: A better way for optical and infrared scene matching via edge point 12

EPM-Net: A better way for optical and infrared scene matchin...

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SPIE 12th International Symposium on Multispectral Image Processing and Pattern Recognition, MIPPR 2023

作者： Huang, Shixiang Chi, Longyun Fu, Wenxing Tian, Jinwen National Key Laboratory of Multispectral Information Intelligent Processing Technology Huazhong University of Science and Technology Wuhan China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (数字)9781510674943

ISBN: (纸本)9781510674936

As a crucial auxiliary technique in inertial navigation, scene matching has been widely applied in aircraft navigation and guidance. To enhance the adaptability and efficiency of scene matching algorithms in complex environments, existing approaches have gradually shifted towards heterogeneous scene matching, such as optical/ infrared scene matching based on deep learning features, with a focus on point features. However, due to the complex and diverse nonlinear distortions between optical and infrared images, the matching accuracy often fails to meet the practical requirements of navigation and positioning. In view of this problem, an EPM-Net algorithm based on edge features is proposed to improve matching performance by extracting more stable and discriminative edge point descriptors. Experimental results on infrared datasets demonstrate that this method achieves an average matching accuracy improvement of more than four times compared to traditional and existing deep learning methods. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Deep learning

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A Grey Wolf Optimizer Variant with Weighted-leader Strategy 24

A Grey Wolf Optimizer Variant with Weighted-leader Strategy

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3rd International Conference on Signal Processing, Computer Networks and Communications, SPCNC 2024

作者： Liang, Yajun Yan, Su Ma, Qian Huang, Shunlun Liu, Xin China Aerodynamics Research & Development Center Sichuan Mianyang China Science and Technology on Complex Aviation Systems Simulation Laboratory Beijing China State Key Laboratory of Air Traffic Management System Beijing China Beijing Aviation Meteorological Institute Beijing China

ISBN: (纸本)9798400710834

To enhance the convergence capability of grey wolf optimizer (GWO), this research investigates an evolved GWO using weighted-leader strategy (WLS), namely WLSGWO. The key issue of WLS is realizing the adaptive adjustment of position weighting according to the control parameters, thus well overcoming the drawback of premature convergence in the basic GWO. The newly developed method’s performance is assessed through experiments conducted on a standardized test suite. Additionally, comparisons are made by utilizing GWO alongside other advanced optimization techniques. The results of non-parametric studies validate the outperformance of the WLSGWO, thus proving the efficiency of the proposed strategy. © 2024 Copyright held by the owner/author(s).

关键词： Swarm intelligence

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Multi-UAV Cooperative Path-Planning under complex Threat Environment 42

Multi-UAV Cooperative Path-Planning under Complex Threat Env...

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42nd Chinese Control Conference, CCC 2023

作者： Liu, Zhenchang Liu, Yuting Zhao, Hongyin Lu, Hanchen Hao, Mingrui Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (纸本)9789887581543

This paper proposes a cooperative path-planning method based on multi-Dubins path segments to meet the penetration requirements of UAVs in a complex threat environment. A pruning strategy is used in path-planning to sift path segments, and the diversity of threat avoidance paths is considered under a reasonable calculation amount. A threat intrusion strategy is designed for no safety path condition, which makes the cooperative path-planning method have excellent robustness. A cooperative path optimization method based on particle swarm optimization is adopted for the path length and collision avoidance requirements. The simulation results show that the UAV cooperative paths can avoid the threat area under any starting and ending points, and path lengths are close to the expected length. © 2023 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Unmanned aerial vehicles (UAV)

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An Improved MPCA Algorithm with Weight Matrix Based on Many-Objective Optimization 1

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17th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2022

作者： Huang, Jianrou Zhang, Jingbo Wang, Qian Cai, Xingjuan Complex System and Computational Intelligent Laboratory Taiyuan University of Science and Technology Taiyuan030024 China

ISBN: (数字)9789819915491

ISBN: (纸本)9789819915484

Data compression and dimensionality reduction play an essential role in machine learning. In recent years, due to the relatively high dimensionality of data, dimensionality reduction based on vectors cannot be well processed and will destroy the structure of high-dimensional data. Therefore, research on dimensionality reduction based on tensors is increasing daily. This paper mainly studies the extended multi-linear principal component analysis (MPCA) of principal component analysis (PCA) in the tensor space. This paper proposes a MPCA dimension reduction algorithm based on the weight matrix, followed by the construction of a multi-objective model. An IP-NSGA-III is proposed to solve the weight matrix. Experimental results of hyperspectral image classification show that, compared with different algorithms, the MPCA algorithm based on the weight matrix proposed in this paper has a better dimension-reduction effect. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Principal component analysis

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Distributed Cooperative Search Based on DRH-NSGA Under Communication Constraint

Distributed Cooperative Search Based on DRH-NSGA Under Commu...

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International Conference on Guidance, Navigation and Control, ICGNC 2022

作者： Si, Jia Shuai Cheng, Jin Hao, Ming Rui Liu, Zhen Chang Science and Technology On Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (纸本)9789811966125

For unmanned aerial vehicle (UAV) cooperative search mission under communication distance limitation environment, considering that the computation scale of rolling time domain optimization increases exponentially with the change of predicted steps and the problem that searching performance metrics are difficult to be selected, the distributed receding horizon non-dominated sorting genetic algorithm (DRH-NSGA) is proposed, and the distributed receding horizon (DRH) process is optimized by non-dominated sorting genetic algorithm (NSGA),and the cooperative search problem in dynamic environment is solved. Firstly, the motion and sensor models of UAV are established. Considering the possibility of interference or communication interruption during UAV communication, the communication interruption probability is added based on the communication distance constraint. In this paper, the environment awareness map is constructed, considering the motion characteristics of time-sensitive targets, and based on the updating of target probability by using Bayesian theory, the updating of time-sensitive target prediction transition probability is added to improve the accuracy of moving target existence probability map. Finally, the search performance index is designed reasonably, and the RH framework is used to optimize the search path. The simulation results show that the distributed cooperative search algorithm based on DRH-NSGA can shorten the single step planning time while ensuring the convergence speed and ensure the real-time decision-making of UAV search. At the same time, it can effectively take into account the search of moving targets after covering the search area. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Antennas

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A Service Mining Scheme Based on Semantic for Internet of Things

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Chinese Journal of Electronics 2025年第2期23卷 236-242页

作者： Xinming Li Yan Sun The Science and Technology on Complex Electronic System Simulation Laboratory Academy of Equipment Beijing China The School of Computer Science Beijing University of Posts and Telecommunication Beijing China

As the development of Internet of things (IOT), massive sensors have been deployed as the public infrastructure. With the development of in-depth applications in IOT, service discovery and composition are challenges to the end users. To handle this challenge, we develop a service mining scheme based on semantic for IOT to provide users with interesting composite services. In this scheme, services can be combined and recommended to users actively according to the calculation of service similarity and an updatable semantic database. By the results of service similarity, useless compositions can be filtered out so that energy consumption on service flooding will be reduced. The update strategy of semantic database is also given out, by which the composite services can keep up with time and be more applicative. The benefits of the proposed method are that all operations such as calculating, filtering, and updating are simple enough to be performed in sensor networks.

关键词： Smart buildings Databases Filtering Semantics Public infrastructure Ontologies Sensor systems Internet of Things Floods Intelligent sensors

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Research Status and Application of Mission Assignment Method and Cooperative Positioning and Navigation for Cluster Aircraft

Research Status and Application of Mission Assignment Method...

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International Conference on Guidance, Navigation and Control, ICGNC 2022

作者： Danting, Sheng Mingrui, Hao Science and Technology On Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (纸本)9789811966125

In order to solve the problem of multi-aircraft cluster cooperative combat, this paper tries to classify and sum up the existing achievements on task assignment method and cooperative positioning and navigation. Among the distributed methods of task allocation, the contract net-based method of task allocation and the distributed method of simulating the complex and orderly collective behavior of social creatures are briefly described. According to the method of cooperative positioning of swarm aircraft, it is divided into measuring the relative distance of aircraft, measuring the relative angle of aircraft and layered cooperative navigation system. Combining with the classical research and application, this paper analyzes and summarizes the existing task allocation methods and the achievements of cooperative positioning and navigation, and forecasts the future engineering application in this field. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Aircraft

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