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4th International Conference on Computer science and Communication technology, ICCSCT 2023

作者： Liu, Yali Xiong, Wei Xiong, Minghui Yu, Xiaolan Liu, Zheng Science and Technology on Complex Electronic System Simulation Laboratory Space Engineering University Beijing101416 China

ISBN: (纸本)9781510671232

The optimization of reconnaissance constellation is an important step in the construction of space-based information system, and the coverage performance is the key index of the optimization of reconnaissance constellation. However, the coverage performance of the current constellation is mostly obtained through the simulation system, which has high time complexity and low efficiency, seriously slowing down the speed of constellation optimization. In order to improve the efficiency of constellation optimization, a two-stage optimization scheme of reconnaissance constellation based on machine learning is proposed. First, the trained machine learning prediction model is combined with the evolutionary algorithm to carry out rough optimization of the reconnaissance constellation, and the decision variable space after the scope is reduced is obtained. Then, in the reduced decision variable space, the simulation system and evolutionary algorithm are used to further optimize the problem, and the final result is obtained. The scheme proposed in this paper speeds up the convergence of population by reducing the search space of decision variables, thus improving the optimization efficiency. By comparing the optimization results of this scheme with those of the traditional scheme, it is found that the proposed scheme is 78.21% shorter than that of the traditional scheme under the premise that the quality gap between the optimization results of the traditional scheme and the traditional scheme is acceptable, which greatly improves the optimization speed of the reconnaissance constellation, and verifies the effectiveness and advancement of the proposed scheme. © 2023 SPIE.

关键词： Multiobjective optimization

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Research on Modeling of spatial information Network based on combat ring 3

Research on Modeling of spatial information Network based on...

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3rd International Conference on Digital Signal and Computer Communications, DSCC 2023

作者： Di, Lu Zhongwen, Zhao Yaru, Wang Science and Technology on Complex Electronic System Simulation Laboratory Space Engineering University Beijing101416 China

ISBN: (数字)9781510666566

ISBN: (纸本)9781510666559

Spatial information network itself is a comprehensive information network with multiple functions, which plays an important role in information acquisition, attack support, navigation and positioning, etc. In order to describe the function of spatial information network in detail, the combat ring theory is introduced to model the nodes, inter-satellite links and earth-satellite links of the network. At the same time, due to its complex and dynamic nature, Different from conventional combat network, the time accumulation graph model is introduced to further describe the network model, so as to truly reflect the support and attack capability of spatial information network under the combat background. © 2023 SPIE.

关键词： Graph theory

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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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MTL-JER: Meta-Transfer Learning for Low-Resource Joint Entity and Relation Extraction 3

MTL-JER: Meta-Transfer Learning for Low-Resource Joint Entit...

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3rd International Conference on Neural Networks, Information and Communication Engineering, NNICE 2023

作者： Peng, Da Pei, Zhongmin Mo, Delin Space Engineering University Science and Technology on Complex Electronic System Simulation Laboratory Beijing China Institute of War Studies Academy of Military Sciences

ISBN: (纸本)9798350335972

Joint entity and relation extraction has achieved impressive advances in NLP, such as document understanding and knowledge graph construction. The typical methods for entity and relation extraction typically break down the joint task into several smaller components or stages for ease of implementation, but this leads to a loss of the interconnected knowledge in the triple. Hence, we propose to model the triple in one module jointly. Furthermore, the labeling of a joint entity and relation extraction tasks is costly and domain-specific;therefore, it is important to improve its performance on low-resource data and domain adaption. To address this issue, we suggest using two sources that are rich in information, namely pre-trained models on large data and multi-domain text corpora. Pretraining allows us to provide the model with the fundamental ability to perform joint entity and relationship extraction. Second, through meta-learning on multi-domain text, we can improve the model's generalization capabilities, enabling it to perform well even with limited data. We present MTL-JER, a Meta-Transfer Learning method for Joint Entity and Relation Extraction in low-resource settings in this paper. Using exhaustive experiments on five datasets, we prove that our model obtains optimal results. © 2023 IEEE.

关键词： Extraction

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Nonlinear impedance control with trajectory adaptation for collaborative robotic grinding

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science China(Technological sciences) 2023年第7期66卷 1928-1936页

作者： HAN FengTao TAM SikYuen CAO ZhiHong ZHAO XingWei TAO Bo DING Han State Key Laboratory of Intelligent Manufacturing Equipment and Technology School of Mechanical Science and EngineeringHuazhong University of Science and TechnologyWuhan 430074China State Key Laboratory of Intelligent Manufacturing System Technology for Complex Products Beijing Institute of Electronic System EngineeringBeijing 100854China ROKAE(Beijing)Technology Co. Ltd.Beijing 100193China

Stiffness adjustment is an important feature of human arm *** adaptive variable impedance control can adapt to the robotic stiffness,but may result in a large *** this paper,nonlinear impedance control is proposed for collaborative robotic grinding,where nonlinear force feedback is designed to compensate for the nonlinear stiffness of the ***,the interaction system can be linearization to ensure the system ***,a target trajectory adaptation strategy is studied to ensure the force tracking ***,switching law between trajectory tracking and force tracking is proposed when the robot performs a complex grinding *** stability of the switch control as well as the trajectory adaptation law is *** are conducted in a robotic grinding test rig,where the robot is used to grind a turbine *** results show that the nonlinear impedance control can obtain stable grinding force,and have better grinding quality than the linear impedance control.

关键词： impedance control robotic grinding trajectory adaptation force tracking

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Multi-View Subspace Clustering Via Simultaneously Cycle Projection and Similarity Learning 21

Multi-View Subspace Clustering Via Simultaneously Cycle Proj...

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21st International Computer Conference on Wavelet Active Media technology and Information Processing, ICCWAMTIP 2024

作者： Tao, Xiang Jie, Liu Wenshen, Qiao Siying, Xiao Mao, Ye Southwest China Institute of Electronic Technology National Key Laboratory of Complex Aviation System Simulation Chengdu610036 China University of Electronic Science and Technology of China Chengdu611731 China

ISBN: (纸本)9798331519254

At present, most of the existing methods combine the data from different views mechanically to obtain the latent subspace with complementary information, which not only fails to make full use of the data information from specific perspectives but also brings redundancy. Therefore, we propose a novel multi-view subspace clustering method. It utilizes cycle projection to obtain a subspace construction model. At the same time, by learning the global structure and local manifold structure of this subspace while assigning learnable weights to different views, the consensus information among views and specific information from different views are captured according to the importance of different views. In this way, our method effectively reduces the original noise and redundancy, and further carries out the improvement of complementarity and consistency among views. The proposed method is optimized by using the Augmented Lagrangian Multiplier with Alternating Direction Minimization (ALM- ADM) algorithm. Experiment results on benchmark datasets confirm the effectiveness of our method. © 2024 IEEE.

关键词： Contrastive Learning

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A Region Preference-based Optimization Algorithm for Satellite Mission Planning Problem 2

A Region Preference-based Optimization Algorithm for Satelli...

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2021 2nd International Conference on Modeling, Big Data Analytics and simulation, MBDAS 2021

作者： Xiong, Minghui Xiong, Wei Science and Technology on Complex Electronic System Simulation Laboratory Space Engineering University China

For the earth observation satellite mission planning problem, objectives such as observed target quantity, observation profit, energy consumption, image quality should be considered simultaneously, which is a many-objective optimization problem. Classical optimization-based mission planning algorithms obtain a set of non-dominated solutions in the entire search space, while only a single satisfy final plan is desired by decision maker. In this paper, a five-objective optimization model for satellite mission planning problem is constructed, then a region preference-based evolutionary algorithm, HMOEA-T, is applied to obtain the desired solutions. The decision makers describe the preference on each objective in target region form, then the algorithm guides a more detailed search within the preference region rather than the entire Pareto front. Comparative studies with preference-based methods (T-NSGA-III) and classical methods (NSGA-III) are conducted. We have exemplified the proposed method manage to obtain the solutions satisfying the mission planning preference and achieve better performance in convergence and diversity. © Published under licence by IOP Publishing Ltd.

关键词： Evolutionary algorithms

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LEO Satellite Network Traffic Forecasting based on ARIMA-BPNN Model 3

LEO Satellite Network Traffic Forecasting based on ARIMA-BPN...

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3rd International Conference on electronic Information Engineering and Computer Communication, EIECC 2023

作者： Han, Chi Xiong, Wei Yu, Ronghuan Fu, Jingyu Space Engineering University Science and Technology on Complex Electronic System Simulation Laboratory Beijing China Jiuquan Satellite Launch Center Jiuquan China

ISBN: (纸本)9798350359961

Satellite network traffic forecasting provides key information for routing and resource allocation, which is important for the efficient operation of satellite network. However, due to the self-similarity and long-range dependence (LRD) of satellite network traffic, traditional linear or non-linear network traffic forecasting models cannot achieve sufficient forecasting accuracy. A combined model of satellite network traffic forecasting based on BPNN and ARIMA is proposed. BPNN is adopted to forecast the residuals. EMD-ARIMA and BPNN forecasting results are combined to achieve satellite network traffic forecasting. Experimental results on the satellite network traffic data generated by the ON/OFF model show that forecast accuracy of the proposed method is better than traditional model, which verifies the effectiveness of the proposed satellite network traffic forecast model. © 2023 IEEE.

关键词： BP neural network empirical mode decomposition intrinsic mode function long-range dependence satellite network

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Research on the Construction Method of Knowledge Graph 3

Research on the Construction Method of Knowledge Graph

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2022 3rd International Conference on Computer Information and Big Data Applications, CIBDA 2022

作者： Xia, Xudong Yu, Ronghuan Science and Technology on Complex Electronic System Simulation Laboratory Space Engineering University Beijing China

ISBN: (纸本)9783800758760

With the continuous innovation of Internet technology, the explosive growth of information has become one of its most obvious characteristics, and how to break through the problem of data storage has become an urgent challenge to be solved. The knowledge graph proposed by Google can intuitively describe the relationship between entities in the objective world in the form of a graph, which is of great help in solving this problem. Firstly, the basic concept of knowledge graph is expounded, and include the key steps of knowledge extraction, knowledge fusion, knowledge storage, etc. Taking the relationship between confirmed cases of the coronavirus disease 2019(COVID-19) in a certain city over the recent period as an example, a knowledge graph of case relationship is constructed. The results indicated that the knowledge graph intuitively shows the transmission path of the epidemic, which can provide certain help for the effective prevention and control of the epidemic. © VDE VERLAG GMBH - Berlin - Offenbach.

关键词： Digital storage

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Current Situation of Denoising And Target Detection In Hyperspectral Images 3

Current Situation of Denoising And Target Detection In Hyper...

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3rd International Conference on Geology, Mapping and Remote Sensing, ICGMRS 2022

作者： Li, Guanzhe Hao, Hongxiong Wu, Lingda Liu, BoYu Space Engineering University Science and Technology on Complex Electronic System Simulation Laboratory Beijing China

ISBN: (数字)9781665485951

ISBN: (纸本)9781665485951

Hyperspectral images technology can greatly enhance the extraction ability of ground object information. It is a research hotspot and frontier field in the field of remote sensing in recent years, and has great application value and broad development prospects in many related fields This paper summarizes the methods of denoising and target detection in hyperspectral *** help researchers better sort out the relevant algorithms. © 2022 IEEE.

关键词： Remote sensing

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