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2021 3rd International Conference on Artificial Intelligence Technologies and Applications, ICAITA 2021

作者： Song, Ani Jia, Xiaoxia Jiang, Wei North China Institute of Computing Technology Beijing100083 China National Key Laboratory for Complex Systems Simulation Department of Systems General Design Institute of Systems Engineering AMS Beijing100083 China

With the development of military intelligence, higher requirements are put forward for automatic term recognition in military field. In view of the characteristics of flexible and diverse naming of military requirement documents without annotated corpus, the method of this paper uses the existing military domain core database, and matches the data set and core database by Aho-Corasic algorithm and word segmentation technology, so that the terms to be recognized in the data set can be divided into three *** possible rules of word formation of military terms are summarized and phrases that conform to the rules of word formation are found in the documents as the term candidate set. The core library and TF-IDF method are used to calculate the value of the candidate terms, and the candidate terms whose value is greater than the threshold are selected iteratively as the real terms. The experimental results show that the F1 value of this method reaches 0.719, which is better than the traditional C-value method. Therefore, the method proposed in this paper can achieve better automatic term recognition effect for military requirement documents without annotation. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Iterative methods

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Decentralized Event-Triggered Online Learning for Safe Consensus of Multi-Agent systems with Gaussian Process Regression

arXiv

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arXiv 2024年

作者： Dai, Xiaobing Yang, Zewen Xu, Mengtian Liu, Fangzhou Hattab, Georges Hirche, Sandra TUM School of Computation Information and Technology Technical University of Munich Munich80333 Germany Robert Koch Institute Berlin Germany National Key Laboratory of Modeling and Simulation for Complex Systems Harbin Institute of Technology 150001 China Department of Mathematics and Computer Science Freie Universität Berlin Berlin Germany

Consensus control in multi-agent systems has received significant attention and practical implementation across various domains. However, managing consensus control under unknown dynamics remains a significant challenge for control design due to system uncertainties and environmental disturbances. This paper presents a novel learning-based distributed control law, augmented by an auxiliary dynamics. Gaussian processes are harnessed to compensate for the unknown components of the multi-agent system. For continuous enhancement in predictive performance of Gaussian process model, a data-efficient online learning strategy with a decentralized event-triggered mechanism is proposed. Furthermore, the control performance of the proposed approach is ensured via the Lyapunov theory, based on a probabilistic guarantee for prediction error bounds. To demonstrate the efficacy of the proposed learning-based controller, a comparative analysis is conducted, contrasting it with both conventional distributed control laws and offline learning methodologies. Copyright © 2024, The Authors. All rights reserved.

关键词： Multi agent systems

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Quantitative analysis of real-time performance and hardware requirements for edge computing platform

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Data Science and Informetrics 2021年第2期1卷 47-63页

作者： Kangkang Shi Gangyong Jia Youhuizi Li Yuyu Yin Congfeng Jiang Li Zhou School of Computer Science Hangzhou Dianzi UniversityHangzhouChina Key Laboratory of Complex Systems Modeling and Simulation Hangzhou Dianzi UniversityHangzhouChina

For real-time edge systems such as autonomous driving,not only the correctness of task functions,but also the response and processing time of tasks should be *** the hardware selection phase of a real-time system,time series analyses must be performed on the hardware platform running real-time *** present,the common method of worst-case execution time(WCET)analysis focuses mainly on analyzing the impact of hardware platform architecture or task execution process on the task running ***,different tasks in an autopilot system have different levels of urgency,and preemption between tasks is the main factor that affects the task execution *** key problem is how to quantify the time fluctuation caused by task preemption for each subtask of the autopilot system running on a fixed hardware *** paper presents a time analysis method for a real-time application based on a queuing theory and preemptive scheduling strategy,which assigns different priorities to tasks according to their time urgency and preemptive scheduling according to task *** an experimental case study,the impact of the running time of each subtask in a real-time application with task priority preemptive scheduling is analyzed,along with the impact of changes in hardware platform performance on such real-time applications.

关键词： Autonomous Driving Queuing Theory Preemptive Scheduling Time Series Analysis

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PID Control for Aeroengine Based on Sparrow Search Algorithm

PID Control for Aeroengine Based on Sparrow Search Algorithm

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2021 China Automation Congress, CAC 2021

作者： Xu, Liang Wang, Hao Liu, Ying Xue, Wei Li, Ningning Tianjin Key Laboratory for Control Theory & Applications in Complicated Systems School of Electrical Engineering and Automation Tianjin University of Technology Tianjin China National Key Laboratory for Complex Systems Simulation Beijing China BeijingAerospace Propulsion Institute Beijing China

ISBN: (纸本)9781665426473

To address the problem of aeroengine PID parameter optimization and tuning, this work employs the excellent performance of the sparrow search algorithm (SSA) with high convergence accuracy and fast convergence speed to propose a self-tuning PID control method (SSA-PID) for aeroengine parameters. Considering that the oil supply output by the actuator may have a substantial overshoot, the proposed technique adds a penalty mechanism for the overshoot at the output, designs and improves the fitness function weighted by performance indicators, and effectively avoids the possible excessive overshoot and sharp oil supply phenomenon of the engine oil supply. The SSA-PID simulates and verifies the mathematical models of the turbofan engine ' s steady-state operating points on the ground and at high altitudes. The results show that the SSA-PID control method has better parameter tuning and optimization effects, a faster speed step response, and generates a fuel supply that does not have a large overshoot, thereby proving its effectiveness and feasibility. © 2021 IEEE

关键词： Three term control systems

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A coevolutionary framework of business-IT alignment via the lens of enterprise architecture

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Journal of systems Engineering and Electronics 2020年第5期31卷 983-995页

作者： LIN Menglong YI Shuanghui ZHANG Mengmeng CHEN Tao CHEN Honghui ZHANG Xiaoxue Science and Technology on Information Systems Engineering Laboratory National University of Defense TechnologyChangsha 410072China National Key Laboratory for Complex System Simulation Academy of Military SciencesBeijing 100000China

Due to the turbulent external business environment, the complexity of internal relations of the organization and the emergence of subversive IT roles, the business-IT alignment(BITA)has become increasingly difficult. The unsuccessful realization of BITA will lead to the waste of organizational resources, the reduction of return on investment and eventually the loss of competitive advantage. In recent years, coevolution has received widespread attention due to its ability to describe the dynamic relationship between IT and business. Multiple principles such as quickening learning action loops and adopt suitable organizing principles for achieving business and IT coevolution(BITC) are obtained. However, the continuous BITC is still hard to be achieved because of the lack of complete BITC management. This paper focuses on the management process of the BITC and how to perform it gradually. A coevolution framework combines the enterprise architecture(EA) approach with the coevolution analysis is proposed, which contains the design of EA, the sensing and governance of the misalignment and the procedure of the EA misalignment *** steps for the governance and prevention of misalignment are discussed in particular. Through comparison with the principles,characteristics and methods of coevolution in the literature, the proposed framework is evaluated. The results show that the proposed framework is effective for BITC implementation.

关键词： business-IT alignment(BITA) coevolution misalignment governance misalignment prevention enterprise architecture

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ISAR Image-based Spatial Target Recognition

ISAR Image-based Spatial Target Recognition

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Information Technology,Big Data and Artificial Intelligence (ICIBA), International Conference on IEEE International Conference on

作者： Yongjing Zhou Weigang Zhu Yonghua He Yonggang Li Department of Electronics and Optics University of Aerospace Engineering Beijing China Key Laboratory of Complex Electronic Systems Simulation Beijing China Graduate School of Aerospace Engineering Beijing China

With the increasing demand for space situational awareness and space environment monitoring, space target discovery, tracking, identification and classification technologies have been developed accordingly. At present, the integrated development of machine learning, artificial intelligence and other multidisciplinary disciplines has greatly promoted the progress of space target detection and identification technology. The inverse synthetic aperture radar image can reflect the fine structural features of space targets, which is important for feature extraction and recognition and classification of space targets. In this paper, three aspects of target recognition technologies based on RCS, HRRP and ISAR imaging are reviewed respectively, and the target recognition methods based on ISAR images are mainly discussed and validated. First, the basic problems and common methods of current RCS, HRRP, and ISAR image target recognition are introduced; then, a summary is made for ISAR image target recognition techniques; finally, the still existing problems of current ISAR image target recognition and the next development prospects are discussed.

关键词：

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Research on Image Stitching Methods for Cmos Grayscale Cameras in Industrial Scenarios

SSRN

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SSRN 2024年

作者： Liu, Qi Huo, Ju Tang, Xiyu Xue, Muyao School of Electrical Engineering and Automation Harbin Institute of Technology Harbin150001 China National Key Laboratory of Modeling and Simulation for Complex Systems Heilongjiang Harbin150000 China School of Astronautics Harbin Institute of Technology Harbin150001 China Space Propulsion Technology Research Institute Shanghai Academy of Spaceflight Technology Shanghai201109 China

Addressing the limited field of view of CMOS grayscale cameras, complex lighting conditions, and the paucity of image features in industrial applications, this paper proposes a novel image stitching method for CMOS grayscale cameras under varying lighting conditions. It extends the camera's field of view while maintaining the interpretability of image features, thus enhancing the robustness and generalizability of image stitching across diverse lighting environments and feature-sparse settings. In the feature extraction phase, a hybrid deep feature extraction network is designed. By employing a deep learning-based approach for feature extraction, the network ensures an ample quantity of features. Building upon this, a line feature selection and reconstruction method is developed to further refine feature matching accuracy, increasing the number of matching lines under extreme lighting and feature-scarce situations, thereby enriching the image features for subsequent stitching steps. The subsequent image transformation phase introduces planar feature constraints;matching feature points and lines generate planar features, addressing alterations in the collective shape of planes common in industrial image stitching. The paper concludes with quantitative evaluation metrics for planar feature-based stitching. Experimental results validate the effectiveness and feasibility of our approach for image stitching of CMOS grayscale cameras under varied lighting conditions and in feature-deficient industrial settings. It offers a viable solution to the challenges of limited imaging fields of view faced by CMOS grayscale cameras in industrial applications. © 2024, The Authors. All rights reserved.

关键词： Feature extraction

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Enhancing realism in LiDAR scene generation with CSPA-DFN and linear cross-attention via Diffusion Transformer model

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Neural Networks 2025年 189卷 107503页

作者： Ye, Shaoxun Di, Xiaoguang Liao, Ming Li, Ximing Control and Simulation Center Harbin Institute of Technology Harbin150080 China National Key Laboratory of Modeling and Simulation for Complex Systems Harbin150080 China

Point cloud diffusion models have found extensive applications in autonomous driving and robotics. However, there is still a big gap between their generated LiDAR scene samples and real-world data in terms of visual quality. This discrepancy primarily arises from the loss of detailed information during the decoding process from latent space and the lack of guidance from global 3D structural information in the point cloud generation process, leading to distortions and artifacts in LiDAR scene samples. In this paper, we propose a novel LiDAR Diffusion Transformer Model that integrates Channel-Spatial Parallel Attention and Dilation Fusion Network (CSPA-DFN) with a linear cross-attention post-processing module to refine the generated LiDAR scene samples. Specifically, CSPA-DFN is designed to simultaneously emphasize detailed features across different channels and spatial locations in parallel, leveraging multi-scale dilated convolutions and channel grouping to preserve and enhance these detailed features. In order to provide global 3D structural information and balance performance and efficiency, we design a post-processing module that fuses voxelized features and range images using a linear ReLU cross-attention mechanism. Our approach is evaluated on the unconditional generation task using the KITTI-360 and nuScenes datasets, achieving the state-of-the-art results in LiDAR scene's generation quality. Furthermore, by incorporating semantic labels and camera views into the latent space, in addition to enhancing the model's semantic understanding capability for LiDAR scenes, our method also demonstrates additional performance improvements compared to previous works in terms of LiDAR scene's visual quality. The code implementation has been released on https://***/HITysx/LiDAR-Scene-Generation. © 2025 Elsevier Ltd

关键词： Photointerpretation

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An ADI Finite Volume Element Method for a Viscous Wave Equation with Variable Coefficients

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Computer modeling in Engineering & Sciences 2020年第5期123卷 739-776页

作者： Mengya Su Zhihao Ren Zhiyue Zhang School of Mathematical Sciences Jiangsu Provincial Key Laboratory for Numerical Simulation of Large Scale Complex SystemsNanjing Normal UniversityNanjing210023China.

Based on rectangular partition and bilinear interpolation,we construct an alternating-direction implicit(ADI)finite volume element method,which combined the merits of finite volume element method and alternating direction implicit method to solve a viscous wave equation with variable *** paper presents a general procedure to construct the alternating-direction implicit finite volume element method and gives computational *** error estimate in L2 norm is obtained for the *** with the finite volume element method of the same convergence order,our method is more effective in terms of running time with the increasing of the computing *** experiments are presented to show the efficiency of our method and numerical results are provided to support our theoretical analysis.

关键词： Viscous wave equation alternating direction implicit finite volume element method error estimates L2 norm

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A PREA and OODA Computing Framework of Unmanned systems to Perform complex Tasks

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年 1-18页

作者： Yang, Dongsheng Yu, Lei Zhang, Yi Zhu, Fenghua Li, Qiang Cui, Huachao Ma, Qiongmin Fan, Lili Tian, Yonglin Jinan University Guangzhou China Intelligent Science & Technology Academy Limited of CASIC Beijing China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China 28th Research Institute of China Electronics Technology Group Corporation Nanjing China National Key Laboratory for Complex Systems Simulation National University of Defense Technology Changsha China School of Information and Electronics Beijing Institute of Technology Beijing China

A C2 computing framework for unmanned systems to perform complex tasks is proposed using methods of system of systems engineering, which is formed by combining the macro-scale command and control (C2) process mechanism model (PREA loop) and micro-scale C2 process mechanism model (OODA loop). Guided by PREA loop and OODA loop, the computing framework is divided into four steps and three kinds of transformations. The four steps are design, construction, operation monitoring, and assessment. The three transformations are tactical feedback, campaign feedback, and strategic feedback. A C2 organization model of joint landing combat force is established against the background of a typical complex task of joint landing operation, and the C2 computing framework based on the PREA &OODA is used to implement the C2 activities of the joint landing combat force. The influence of the computing framework on the performance of unmanned systems under different task conditions is verified, including task coordination load, task efficiency and sensitivity of unmanned systems response. Authors

关键词： Feedback

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