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5th International Conference on Industrial Artificial Intelligence, IAI 2023

作者： Wang, Jiangtao Sun, Zewen Li, Peng Sun, Liang University of Science and Technology Key Laboratory of Intelligent Bionic Unmanned Systems of Ministry of Education School of Intelligent Science and Technology Beijing100083 China University of Science and Technology Beijing Key Laboratory of Urban Underground Space Engineering Beijing100083 China

ISBN: (纸本)9798350325294

Aiming at the problems of insufficient intelligence level, computational complexity, and lack of autonomous learning capability of traditional path planning algorithms, this paper proposes a solution for implementing the motion path planning of agent using proximal policy optimization algorithm based on deep reinforcement learning. The solution can provide a universal method for the path planning of agent moving in a two-dimensional plane, which splits the task into two subtasks: path generation and path tracking, where the agent generates a feasible path based on proximal policy optimization algorithm, and the path tracking task can be implemented by a traditional control algorithm. Finally, the proposed algorithm is simulated and verified in training and testing environments. The results show that the proposed algorithm can effectively complete the path generation task, and the proximal policy optimization algorithm has advantages over the A∗ algorithm in terms of intelligence level and environmental adaptability. Furthermore, the algorithm is generalizable to all movable objects. © 2023 IEEE.

关键词： Motion planning

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Research on extremely weak remanence measurement system 3

Research on extremely weak remanence measurement system

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2023 3rd International Conference on Measurement Control and Instrumentation, MCAI 2023

作者： Xu, Chaoqun Sun, Tian Huang, Kui Xiao, Qi Laboratory of Space Magnetism and Applications Beijing Institute of Spacecraft Environment Engineering Beijing China Department of Science and Technology Development Systems Engineering Research Institute Beijing China

To accurately obtain the extremely weak magnetic field information of the test piece, this article first introduces the basic principles of the extremely weak residual magnetic field measurement technology. Then, an ultra-high precision magnetic shielding system has been developed, which is made of high permeability materials and equipped with a demagnetization coil system, and it can regularly eliminate the inductance of the entire shielding system. The effective shielding inner diameter of the magnetic shielding system is 0.8 m, the length is 1.6 m, and the magnetic field resolution is 0.0015 nT. This system can provide strong support for the measurement of extremely weak magnetic fields in materials and biomedical magnetic research. © Published under licence by IOP Publishing Ltd.

关键词： Magnetic shielding

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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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Optimizing Cost-Efficient SFC Routing in NTNs: A Novel Transformer-Ant Colony Optimization Framework

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IEEE Transactions on Vehicular technology 2024年第5期74卷 8037-8051页

作者： Li, Yuanfeng Zhang, Qi Yao, Haipeng Xin, Xiangjun Zhao, Yi Gao, Ran Beijing Key Laboratory of Space-ground Interconnection and Convergence State Key Laboratory of Information Photonics and Optical Communications School of Electronic Engineering Beijing100876 China National University of Defense Technology Science and Technology on Information Systems Engineering Laboratory Changsha410073 China School of Information and Communication Engineering Beijing100876 China Beijing Beijing102300 China Beijing Institution of Technology School of Information and Electronics Beijing100081 China

Non-Terrestrial Networks (NTN), including Low Earth Orbit (LEO) satellite constellations, aim to provide connectivity to remote and underserved areas. These networks now support complex network services leveraging Service Function Chaining (SFC), which sequences service functions such as firewalls and load balances to customize network behavior. In this paper, a comprehensive system model for SFC deployment in NTN is presented. The SFC deployment problem is regarded as comprising two parts: routing and VNF embedding. To improve the cost efficiency of SFC deployment in NTN, a Transformer-Ant Colony Optimization approach has been proposed. The employment of the Transformer architecture to encode SFC requests and the assistance of ACO with neural network modules in identifying optimal paths for VNF embedding are pioneered in this work. The simulation results confirm that our approach achieves superior performance in terms of cost, communication success rate, and delay, demonstrating its potential for efficient SFC deployment in NTN scenarios. © 1967-2012 IEEE.

关键词： Ant colony optimization

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A Light Gradient Boosting Machine Based Effectiveness Prediction Method of space Reconnaissance System

A Light Gradient Boosting Machine Based Effectiveness Predic...

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IEEE Advanced Information technology, Electronic and Automation Control Conference (IAEAC)

作者： Jiahuan Liu Ping Jian Science and Technology on Complex Electronic System Simulation Laboratory Space Engineering University Beijing China

To address the problem of effectiveness evaluation of space reconnaissance systems with limited data sets, vast array of indexes and inadequate model interpretability, an interpretable effectiveness prediction method based on Light Gradient Boosting Machine(LightGBM) and the Shapley Additive exPlanations(SHAP) is proposed. The thorough evaluation process is given and the index system of space reconnaissance systems is built. Then LightGBM is used to establish a nonlinear mapping the model between the indexes and the effectiveness. Additionally, the model’s hyperparameters are adjusted using Bayesian optimization to improve accuracy and lessen computational load. Furthermore, the feasibility of the proposed method is validated by modeling and evaluating the performance of the space reconnaissance system under a particular operational scenario. The experimental results show that compared with other mainstream machine learning methods, the proposed method has higher prediction accuracy and can efficiently extract the potential characteristics of the space reconnaissance system.

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Adaptive Broad Learning Network for LPI Radar Waveform Recognition 9

Adaptive Broad Learning Network for LPI Radar Waveform Recog...

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9th International Conference on Intelligent Computing and Signal Processing, ICSP 2024

作者： Wang, Dong Cui, Tianshu Li, Ruike Huang, Yonghui Zhu, Yan National Space Science Center Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China China Academy of Aerospace Science and Innovation Beijing China Key Laboratory of Electronics and Information Technology for Space Systems Beijing China

ISBN: (纸本)9798350376548

Low probability of intercept (LPI) radar waveform recognition is a crucial branch in the field of electronic reconnaissance, serving as a vital method for acquiring information from non-cooperative radar sources. In recent times, deep learning models have demonstrated significant breakthroughs in the field of LPI radar waveform recognition (LWR). While these models significantly enhance recognition accuracy, the abundance of parameters and computations in the model renders training time-consuming, and the model structure lacks flexibility and scalability. To address these challenges, we propose an adaptive broad learning network (ABLN) for LWR. The ABLN transforms the time-frequency images (TFIs) of radar signals into feature nodes and enhancement nodes, with waveform types represented as output nodes. We further introduced a strategy for adaptively adjusting network parameters to reduce computational overheads, facilitating expedited optimization of the model structure. The simulation results show that ABLN has superior performance compared with other LWR methods. © 2024 IEEE.

关键词： Image enhancement

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Modeling the dynamic alignment of business and information systems via the lens of human-centered architecture evolution

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Journal of systems Engineering and Electronics 2021年第4期32卷 881-888页

作者： ZHANG Mengmeng YI Shuanghui CHEN Honghui LUO Aimin LIU Junxian ZHANG Xiaoxue Science and Technology on Information Systems Engineering Laboratory National University of Defense TechnologyChangsha 410072China National Key Laboratory for Complex System Simulation Military Academy of SciencesBeijing 100080China

The complexity of business and information systems(IS)alignment is a growing concern for researchers and practitioners *** extant research on alignment architecture fails to consider the human viewpoint,which makes it difficult to embrace emergent *** paper contributes to the extant literature in the following ***,we combine an enterprise architecture(EA)framework with a human viewpoint to address alignment issues in the architecture design phase;second,we describe a dynamic alignment model by developing a humancentered meta-model that explains first-and second-order changes and their effects on alignment *** paper provides better support for the theoretical research and the practical application of dynamic alignment.

关键词： business and information systems(IS)alignment human viewpoint enterprise architecture(EA) meta-model dynamic alignment

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Evolutionary Interest Representation Network for Click-Through Rate Prediction

Evolutionary Interest Representation Network for Click-Throu...

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2023 IEEE International Conference on Web Services, ICWS 2023

作者： Zhou, Renjie Jin, Zhenming Wan, Jian Zhang, Jilin Guo, Xingyu Liu, Qiang Hangzhou Dianzi University Key Laboratory of Complex Systems Modeling and Simulation of the Ministry of Education School of Computer Science and Technology Hangzhou China Hangzhou Dianzi University Key Laboratory of Complex Systems Modeling and Simulation of the Ministry of Education Itmo Joint Institute Hangzhou China Zhejiang University of Science and Technology School of Information and Electronic Engineering Hangzhou China Zhejiang Police College Dept. of Computer and Information Technology Hangzhou China

ISBN: (纸本)9798350304855

The rapid development of the Internet has revo-lutionized our lives, providing us with an array of convenient services. However, this revolution has also led to the problem of data overload. Personalized recommendation services have been widely recognized as an effective solution to this problem by both the industrial and academic communities. Accurate prediction of click-through rate (CTR) is a critical task in personalized recommendation systems since it can improve the user's shopping experience, ultimately increasing revenue for the platform. To achieve accurate CTR prediction, it is crucial to capture user interests. While several methods for interest modeling exist, challenges related to user interest evolution and user behavior noise need further attention. This paper proposes a novel CTR prediction model named the Evolutionary Interest Representation Network (EIRN), which learns the evolving interest representation of users from their behaviors, profiles, and environmental attributes. In the model, we introduce an advertisement correlation graph decomposition layer and a noise filter layer to enhance and purify the user behavior representation. An interest extraction layer is designed to capture sequential correlations and common characteristics between user behaviors, representing their interests. Additionally, as user interests evolve over time and their importance changes, an attention-based interest evolution layer is designed to track the evolution of user interests. Our proposed method is validated using four public datasets and an industrial dataset, showing its superiority over existing CTR prediction methods. © 2023 IEEE.

关键词： Forecasting

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InterMap-NRTI: A Novel Radio Tomographic Imaging Positioning Model Based on the Intersection Map of Wireless Links

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IEEE Transactions on Vehicular technology 2025年第5期74卷 6954-6965页

作者： Wang, Bobo Ma, Yongtao Zhang, Xianchao Zhang, Jing Huang, Zixuan University of Science and Technology of China School of Cyber Science and Technology Anhui Hefei230027 China Tianjin University School of Microelectronics Tianjin300072 China Jiaxing University Provincial Key Laboratory of Multimodal Perceiving and Intelligent Systems Engineering Research Center of Intelligent Human Health Situation Awareness of Zhejiang Province Jiaxing314001 China University of Science and Technology of China Science Island Branch of Graduate School Anhui Hefei230031 China Institute of Space Integrated Ground Network Anhui Hefei230088 China Zixuan Huang is with the Institute of Space Integrated Ground Network Anhui Hefei230088 China

Device-free localization (DFL) is a potential positioning technique that can localize targets without requiring any device. Radio tomographic imaging (RTI) is one of the most favorable DFL methods and has many advantages over other methods. In multi-target localization indoors, target-affected wireless signal is inevitably contaminated with non-negligible interference of noise and complex multipath. Existing RTI positioning models utilize contaminated signals for multi-target localization, resulting in low positioning performance. To decrease the effect of contaminated signals, we propose a novel RTI positioning model based on the intersection map of wireless links (InterMap-NRTI). InterMap-NRTI utilizes the statistical method to determine wireless links mainly affected by targets and the interpolation method to complement the wireless links that are interrupted due to hardware malfunction and targets' obstruction. The next step is to formulate the definitions to extract high-intersections closest to the target based on the intersection map of target-affected links. Subsequently, we establish a novel positioning model based on signal strengths of wireless links and high-intersections in each cluster determined by DBSCAN algorithm using a saddle surface model. Finally, Hooke-Jeeves method is used to search for the optimal solution of the positioning model. The experiment shows that InterMap-NRTI's accuracy and identification accuracy rate outperforms other methods by an average of more than 30% and more than 14%, respectively, and InterMap-NRTI has a good tolerance for scenario layout. © 2025 IEEE.

关键词： UHF devices

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Evaluation of Joint Information Environment Service Capability of space-based Network Information System Based on ANP-Fuzzy Comprehensive Evaluation Method 10

Evaluation of Joint Information Environment Service Capabili...

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10th IEEE Joint International Information technology and Artificial Intelligence Conference, ITAIC 2022

作者： Han, Chi Jian, Ping Xiong, Wei Fu, Jingyu Aerospace Information Institute Space Engineering University Beijing China Science and Technology on Complex Electronic System Simulation Laboratory Space Engineering University Beijing China

ISBN: (数字)9781665422079

ISBN: (纸本)9781665422079

In the increasingly systematic and networked environment of aerospace equipment, the space-based information service capability is not only affected by the platform and payload capacity of the mission spacecraft, but also increasingly restricted by the network characteristics and network environment for space-based information acquisition. In this context, the joint information environment of the space-based network information system is constructed (JIESNIS). The service capability evaluation index system of JIESNIS is constructed pertinently. Analytic Network Process (ANP) and fuzzy comprehensive evaluation method are combined to evaluate the service capability of JIESNIS. Based on the background of the space-based network information system joint information environment support operation under the customized and active service mode, the simulation model is constructed. The proposed ANP-Fuzzy comprehensive evaluation method is adopted to evaluate the capability JIESNIS, meanwhile the effectiveness of the method is verified. © 2022 IEEE.

关键词： Information services

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