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Learning-Based Perimeter Invasion Design with Partial information of Defense Model

IFAC-PapersOnLine 2023年第2期56卷 1319-1324页

作者： Yan Zhong Yushan Li Xiaopeng Wang Chongrong Fang Jianping He The Dept. of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China NSFOCUS Technologies Group Co. Ltd Beijing China

This paper focuses on the learning-based perimeter-defense problem. Specifically, we consider a scenario where an attacker invades an area protected by a defender with only partial information about the target area and defense strategy. The attack design is challenging since the flexible and unknown defense strategy results in the highly uncertain feasible invasion space. To address the problem, we propose a learning-based method by using patrol and defense trajectories. First, we apply an ellipse fitting method to regress the perimeter of the protected area with piecewise elliptic segments. Then, we characterize the defense behaviors into different patterns and learn the conditions to activate different strategies by tentative invasions. Finally, we design a model predictive controller to solve the optimal invasion trajectory planning. Simulations are provided to illustrate the feasibility and effectiveness of the proposed method.

关键词： Perimeter-defense learning model-predictive control control design

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Viscoplastic constitutive model of a nickel-based superalloy under multiaxial loading conditions

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Journal of Iron and Steel Research International 2021年第9期28卷 1190-1202页

作者： Wen-bin Jia Xin Li Zhi Chen Kai Zhao Lei Fang Key Laboratory of Aero-Engine Thermal Environment and Structure Ministry of Industry and Information TechnologyJiangsu Province Key Laboratory of Aerospace Power SystemState Key Laboratory of Mechanics and Control of Mechanical StructuresCollege of Energy and Power EngineeringNanjing University of Aeronautics and AstronauticsNanjing210016JiangsuChina

Based on Chaboche constitutive model,a viscoplastic constitutive model of nickel-based alloy under multiaxial loading is proposed by introducing Lemaitre damage model and non-proportional hardening *** damage model can characterize the effect of microscopic defects on the fatigue behavior and non-proportional hardening factor is used to describe non-proportional hardening ***,the stress–strain hysteresis loops at room and high temperatures under different loading conditions are simulated by the proposed constitutive *** between experiments and simulations confirms that the proposed model can reasonably predict the fatigue behavior of nickel-based alloy under different multiaxial *** last,the fatigue life predictions under different multiaxial loadings are investigated,and comparison between experiments and simulations verifies the accuracy of the proposed model.

关键词： Nickel-based alloy Multiaxial loading Viscoplastic constitutive model Lemaitre damage model Non-proportional hardening factor

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Weed detection based on improved Yolov5

Weed detection based on improved Yolov5

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6th International Conference on Intelligent Computing and Signal processing (ICSP)

作者： ZiZheng Yu ZiJun Nie Yong Qi Hu HuangBin Yan LiJun Lou Zhijian Yin Zhen Yang School of Communications and Electronics Jiangxi Science and Technology Normal University Nanchang China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai China

The scale of grain production affects human life and development. With the continuous expansion of cultivated land, the reproductive ability of weeds to mutiply gradually increases, which affects the growth of crops. If weeds are not treated properly managed, they can also allow spread indiscriminately in the field and reduce crop yields. The growth ability of weeds is stronger than that of crops, and there are many types of weeds with a wide of species diversity. To solve the problem that the existing weed detection methods cannot detect and classify weeds accurately and quickly, a deep learning method based on improved Yolov5 was designed for weed detection. By replacing the 3 × 3 convolution with multi-head self-attention (MHSA) in the Yolov5's backbone, the accuracy of weed detection is improved. The experimental results show that the improved Yolov5 weed detection algorithm achieves 51.4% accuracy. Compared with the original Yolov5 model, the calculation amount is 3 points less than the original, and total time required is slightly shorter, which improves the accuracy of weed classification and positioning.

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Smoke Detection In Complex Scenery using Improved YOLOV5

Smoke Detection In Complex Scenery using Improved YOLOV5

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6th International Conference on Intelligent Computing and Signal processing (ICSP)

作者： ZiJun Nie YongQi Hu ZiZheng Yu RuJia Li ZhiJian Yin HuaLin Zhan Zhen Yang School of Communications and Electronics Jiangxi Science and Technology Normal University Nanchang China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai China

Considering smoke detection in a complex scene, high smoke object error rate and low detection efficiency, an improved YOLOV5 for smoke detection is proposed in this paper. To improve the effectiveness of smoke detection algorithm for smoke targets in complex scenes. First, a new lightweight convolution technique GSConv is introduced to replace the Conv layer in the neck layer for feature extraction, and the original C3 module is replaced by Cross Stage Partial Network (GSCSP) module VoVGSCSP. This improvement reduces the computation complexity of the algorithm while maintaining the detection accuracy. Second, CIoU is replaced by SIoU as the regression function of the prediction box to improve the prediction accuracy of the prediction box and reduce the rate of missed detection of the target. Finally, to improve the performance of the deep network, Dynamic ReLU is introduced as an activation function (dynamically adjusting the ReLU parameters depending on the input data). Experiments on the SM-dataset (smoke detection dataset) show that the improved model improves the accuracy and precision of target smoke detection compared to the YOLOV5 model. Its precision is increased by 1.8%, mAP@0.5 is increased by 1.0%, the complexity of the model is reduced by 23.8%. The improved algorithm proposed in this paper can effectively extract smoke features and more suitable for smoke detection tasks in complex scenes.

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Dynamic Template Update Mechanism for Visual Object Tracking

Dynamic Template Update Mechanism for Visual Object Tracking

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6th International Conference on Intelligent Computing and Signal processing (ICSP)

作者： YongQi Hu ZhongWang Cai ZiJun Nie ZiZheng Yu Ying Cao Zhijian Yin Zhen Yang School of Communications and Electronics Jiangxi Science and Technology Normal University Nanchang China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai China

Given the requirements for robust target classification and accurate target state estimation in visual tracking, SiamFC++ proposes a set of practical guidelines for designing high-performance general-purpose trackers by considering the special nature of visual tracking problems. Inspired by dynamic modules, We propose an empirical method for integrating a dynamic module into the image input, which is concatenated with the template module after feature maps are extracted by the backbone network. Since the position and shape of the object can change significantly within a video sequence, the added dynamic module can better focus on the target region of the feature map to obtain better similarity maps. Extensive experiments and comparisons demonstrate that our simple and effective method achieves reliable results on the benchmarks of LaSOT, TrackingNet, and GOT-10K and provides a significant speed advantage in real-time.

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Digital Twin Based Sintering Proportioning: Improved Whale Optimization Method

Digital Twin Based Sintering Proportioning: Improved Whale O...

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Chinese Automation Congress (CAC)

作者： Wei Liu Xuda Ding Xuehan Bai Cailian Chen Xingping Guan Department of Automation Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Jiao Tong University Shanghai P.R. China

Sintering proportion optimization plays a crucial role in determining the final product quality of sintered iron ore. However, the traditional approach of separating the optimization processes between the procurement and technical departments often fails to achieve the global optimum. In this paper, We propose a joint optimization approach for sintering proportioning based on digital twin (DT) technology. To tackle the complex constraints of this joint optimization problem, we develop a multiple improved whale optimization algorithm (MIWOA) that overcomes the issue of getting trapped in local optima. The proposed MIWOA incorporates three strategies, including a nonlinear convergence factor, Levy flight, and Gaussian mutation. Besides, the numerical simulations are conducted in order to analyze the influence of the convergence factors. Finally, various related approaches for sintering proportioning optimization are tested, and DT-based MIWOA achieved the best performance.

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Periodicity in dynamical games driven by the Hedge algorithm and myopic best response 63

Periodicity in dynamical games driven by the Hedge algorithm...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Guo, Xinxiang Mu, Yifen Yang, Xiaoguang University of Chinese Academy of Sciences The Key Laboratory of Systems and Control Institute of Systems Science Academy of Mathematics and Systems Science Chinese Academy of Sciences School of Mathematical Sciences Beijing100190 China Institute of Systems Science Academy of Mathematics and Systems Science Chinese Academy of Sciences The Key Laboratory of Systems and Control Beijing100190 China Institute of Systems Science Academy of Mathematics and Systems Science Chinese Academy of Sciences The Key Laboratory of Management Decision and Information System Beijing100190 China

ISBN: (纸本)9798350316339

In this paper, we consider the n × n two-payer zero-sum repeated game in which one player (player X) employs the popular Hedge (also called multiplicative weights update) learning algorithm while the other player (player Y) adopts the myopic best response. The theoretical analysis on the dynamics of such game system is still rare, which is however of promising interests. We investigate the dynamics of such Hedge-myopic system by defining a metric Q(xt), which measures the distance between the stage strategy xt and Nash Equilibrium (NE) strategy of player X. We analyze the trend of Q(xt) and prove that it is bounded and can only take finite values on the evolutionary path when payoffs are all rational numbers and the game has an interior NE. Based on this, we prove that the stage strategy sequence of both players are periodic after finite stages and the time-averaged strategy of player Y within one period is an exact NE strategy. © 2024 IEEE.

关键词： Consensus algorithm

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Condition Monitoring for Railway Point Machines Based on Sound Analysis and Support Vector Machine

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Chinese Journal of Electronics 2020年第4期29卷 786-792页

作者： SUN Yongkui CAO Yuan XIE Guo WEN Tao School of Electronic and Information Engineering Beijing Jiaotong University National Engineering Research Center of Rail Transportation Operation and Control System Beijing Jiaotong University Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology

Railway point machines(RPMS) are one of the key equipments in the railway system to switch different routes for the *** monitoring for RPMs is a vital measure to keep train operation safe and *** convenience and low cost into consideration, a novel intelligent condition monitoring method for RPMs based on sound analysis is ***-domain and frequency-domain features are obtained,and normalized using z-score standardization method to eliminate the influences of different *** particle swarm optimization(BPSO) is utilized to select the most significant discrimination feature *** effects of the selected optimal features are verified using Support vector machine(SVM), 1-Nearest neighbor(1 NN), Random forest(RF), and Naive Bayes(NB).Experiment results indicate SVM performs best on identification accuracy and computing cost compared with the other three *** identification accuracies on normal switching and reverse switching processes reach100% and 99.67%, respectively, indicating the feasibility of the proposed method.

关键词： Condition monitoring Sound analysis Railway point machines(RPMs) Binary particle swarm optimization(BPSO) Support vector machine(SVM)

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A Method for Compressed Storage and Retrieval of Triplet Data Based on Cuckoo Hashing 21

A Method for Compressed Storage and Retrieval of Triplet Dat...

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21st International Computer Conference on Wavelet Active Media Technology and information processing, ICCWAMTIP 2024

作者： Pengcheng, Liu Qinzhi Shibin, Zhang Yan, Chang Lili, Yan School of Cybersecurity Xin Gu Industrial College Chengdu University of Information Technology Chengdu610225 China Advanced Cryptography and System Security Key Laboratory of Sichuan Province Chengdu610225 China SUGON Industrial Control and Security Center Chengdu610225 China

ISBN: (纸本)9798331519254

This paper proposes a method for compressing and retrieving triple data based on optimized cuckoo hash. Firstly, the optimized cuckoo hash algorithm is utilized to quickly establish node indexes. Then, the relationship information of triples is stored in the form of a sparse matrix according to the relationship type. Finally, the double compression algorithm k2-Rel is employed to compress the relationship attribute matrix of stored triple information, aiming to reduce storage space and lower storage costs. Experimental results demonstrate that the optimized cuckoo hash algorithm significantly reduces the time for building node indexes. Furthermore, utilizing the k2-Rel compression algorithm for compressing the relationship information between nodes substantially decreases storage space, ultimately achieving efficient storage and retrieval of triple data. © 2024 IEEE.

关键词： Cuckoo hash Data compression Knowledge graph Triple data

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Communication-Efficient Personalized Distributed Learning with Data and Node Heterogeneity

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IEEE Transactions on Cognitive Communications and Networking 2025年

作者： Tian, Zhuojun Zhang, Zhaoyang Li, Yiwei Bennis, Mehdi Zhejiang University College of Information Science and Electronic Engineering Hangzhou310027 China University of Oulu Center for Wireless Communications Oulu90014 Finland State Key Laboratory of Industrial Control Technology Hangzhou310027 China Zhejiang Provincial Key Laboratory of Multimodal Communication Networks and Intelligent Information Processing Hangzhou310027 China Xiamen University of Technology Fujian Key Laboratory of Communication Network and Information Processing Xiamen361024 China

To jointly tackle the challenges of data and node heterogeneity in decentralized learning, we propose a distributed strong lottery ticket hypothesis (DSLTH), based on which a communication-efficient personalized learning algorithm is developed. In the proposed method, each local model is represented as the ‌Hadamard product of global real-valued parameters and a personalized binary mask for pruning. The local model is learned by updating and fusing the personalized binary masks while the real-valued parameters are fixed among different agents. To further reduce the complexity of hardware implementation, we incorporate a group sparse regularization term in the loss function, enabling the learned local model to achieve structured sparsity. Then, a binary mask aggregation algorithm is designed by introducing an intermediate aggregation tensor and adding a personalized fine-tuning step in each iteration, which constrains model updates towards the local data distribution. The proposed method effectively leverages the relativity among agents while meeting personalized requirements in heterogeneous node conditions. We also provide a theoretical proof for the DSLTH, establishing it as the foundation of the proposed method. Numerical simulations confirm the validity of the DSLTH and demonstrate the effectiveness of the proposed algorithm. © 2015 IEEE.

关键词： Iterative methods

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