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IASTED International Conference on Applied simulation and Modelling, ASM 2011

作者： Ye, Feng Lan, Guo-Xing Cai, Ye-Quan Zhang, Ying-Chao Science and Technology on Complex Systems Simulation Laboratory Post Box. 9702#19 Beijing 100101 China

ISBN: (纸本)9780889868939

The typical operation flow of complex system has analyzed in this paper. The rehearsal model of the complex system based on the principle of Petri Nets has proposed, and illustrated by the case of OODA. The Petri Nets demonstration prototype under a typical scenario of complex system has built. The method of complex system modeling based on Petri Nets is a possible approach to fit in with the needs of constructing a typical rehearsal system of the complex system by existing simulation models (subsystems) in a short time. It meets the requirements of the demonstration research and evaluation mission for the complex system, which carries out in a short-term action cycle and accomplishes the mission in high efficiency.

关键词： Petri nets

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Research on system of systems simulation optimization

Research on system of systems simulation optimization

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IASTED International Conference on Applied simulation and Modelling, ASM 2011

作者： Lan, Guo-Xing Ye, Feng Science and Technology on Complex Systems Simulation Laboratory Post Box. 9702#19 Beijing 100101 China

ISBN: (纸本)9780889868939

Optimization is one of the most important research contents of System of systems (SoS), and computer simulation technology is an effective means to resolving optimization problem. This paper makes further exploration of SoS description and optimization problem, simulation optimization and its development direction. The multilayer optimization to resolving optimization problem of system and hybrid optimization algorithm based on sensitivity analysis and genetic algorithm has proposed. They are used to offer a technological support for SoS optimization problem.

关键词： Sensitivity analysis

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A grain level model for deformation and failure of ultrafine-grained tungsten

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science China(Technological sciences) 2019年第5期62卷 755-761页

作者： REN Ke CHEN LiRong CHENG YangYang WANG JianXiang DUAN HuiLing State Key Laboratory for Turbulence and Complex Systems Department of Mechanics and Engineering Science College of EngineeringPeking University Key Laboratory of High Energy Density Physics Simulation Center of Applied Physics and Technology BIC-ESAT and IFSA Collaborative Innovation Center of MoE Peking University

Ultrafine-grained tungsten(UFG W) produced by severe plastic deformation technology has many potential applications due to its high strength and ductility. To reveal the mechanism for the high ductility of UFG W, the deformation and failure behaviors of coarse-grained tungsten(CG W) and UFG W have been compared based on a three-dimensional crystal plastic finite element method(CPFEM) simulation. Cohesive element method has been utilized to model the behavior of grain boundaries(GBs). Both plastic deformation in grain interiors and grain boundary opening have been observed in different periods of deformation in UFG W. It is concluded that the high GB density and elongated microstructure in the UFG W suppress crack propagation, decrease the stress concentration and impurity concentration on GBs, therefore enhance the ductility of the material.

关键词： ultrafine grain(UFG) tungsten crystal plasticity interface failure

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Satellite Interference Signal Classification Using Improved MLP Model

Satellite Interference Signal Classification Using Improved ...

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2022 IEEE International Conference on Unmanned systems, ICUS 2022

作者： Xie, Liwei Zhuang, Yaqiang Zhuang, Xuebin Zeng, Xiaohui School of Systems Science and Engineering Sun Yat-Sen University Guangzhou China School of Integrated Circuits and Electronics Beijing Institute of Technology Beijing Key Laboratory of Millimeter Wave and Terahertz Technology Beijing China Science and Technology On Complex Aviation Systems Simulation Laboratory Beijing China

ISBN: (数字)9781665484565

ISBN: (纸本)9781665484565

In response to the existing style of deceptive jamming of Global Position System (GPS) receivers by aerial jammer carriers, a method using improved multi-layer perceptron (MLP) model is proposed to identify and classify interference sources based on the rate of change of satellite incoming angle. The work firstly constructs an airborne GPS interference source localization deployment model, then analyzes and verifies the rationality of this simulation data model, and finally emphasizes the superiority of the proposed method using the classical classification algorithm as a comparison method. The simulation results indicated that the proposed method is capable to identify the corresponding interferers with a greater rate of recognition compared with other method in the built multi-interference source environment, which provides a reference for dealing with the interference identification and classification in the networked GPS interference source deployment environment. © 2022 IEEE.

关键词： Antennas

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A new multi-position calibration method for accelerometers of the inertial navigation system 27

A new multi-position calibration method for accelerometers o...

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27th Chinese Control and Decision Conference, CCDC 2015

作者： Chan, Li Yuan, Cao Zhang, Shi-Feng College of Aerospace Science and Engineering National University of Defense Technology Changsha China Science and Technology on Complex Land Systems Simulation Laboratory Beijing China

ISBN: (纸本)9781479970179

To guarantee success of precision navigation, it is necessary to carry out in-field calibration for the accelerometers of the inertial navigation system (INS) before a mission is launched. Traditional multi-position calibration method for accelerometers of the inertial measurement units (IMU) are carried out through a turntable (Strap-down INS) or the gimbals(platform INS). To achieve high precision calibration results, the position of the turntable (gimbals) need to be locked precisely. However, the high precision positions are difficult to be attained outside the laboratory. Focusing on this problem, a new calibration method is proposed which uses the gravity residual to reduce the effects caused by locking errors of the positions. simulations are conducted to analyze the performance and the sensitivity of the proposed methods. It is proved that the proposed methods can estimate the accelerometer parameter more precisely than traditional multi-position methods. © 2015 IEEE.

关键词： accelerometers gravity residual INS multi-position

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An Improved PC-Kriging Method for Efficient Robust Design Optimization

An Improved PC-Kriging Method for Efficient Robust Design Op...

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作者： Lin, Qizhang Chen, Chao Xiong, Fenfen Chen, Shishi Wang, Fenggang School of Aerospace Engineering Beijing Institute of Technology Beijing100081 China Science and Technology on Complex Aviation Systems Simulation Laboratory Beijing100076 China Beijing Electromechanical Engineering Institute Beijing100074 China

The polynomial-chaos-kriging (PC-Kriging) method has been derived as a new uncertainty propagation approach and widely used for robust design optimization in a straightforward manner, of which the statistical moments would be estimated through directly conducting Monte Carlo simulation (MCS) on the PC-Kriging model. However, the computational cost still cannot be negligible because thousands of statistical moment estimations might be performed during robust optimization, especially for highly nonlinear and complicated engineering problems. An analytical statistical moment estimation method is derived for PC-Kriging in this work to reduce the computational cost rather than referring to MCS. Meanwhile, a sequential sampling strategy is applied for PC-Kriging model construction, in which the sample points are not generated all at once, but sequentially allocated in the region with the largest prediction uncertainty to improve the accuracy of PC-Kriging model as much as possible. Through testing on three mathematical examples and an airfoil robust optimization design problem, it is noticed that the improved PC-Kriging method with analytical statistical moment estimation and sequential sampling strategy is more efficient than the traditional ones, demonstrating its effectiveness and advantage. © Springer Nature Singapore Pte Ltd. 2020.

关键词： Kriging

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Query modeling for click data based image recognition using graph based propagation and sparse coding

Query modeling for click data based image recognition using ...

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9th International Conference on Internet Multimedia Computing and Service, ICIMCS 2017

作者： Wu, Weichen Tan, Min Zheng, Guangjian Yu, Jun Key Laboratory of Complex Systems Modeling and Simulation School of Computer Science and Technology Hangzhou Dianzi University Hangzhou310018 China

ISBN: (纸本)9789811085291

We address the fine-grained image recognition problem using user click data, wherein each image is represented as a semantical query-click feature vector. Usually, the query set obtained from search engines is large-scale and redundant. We propose a novel query modeling approach to merge semantically similar queries and construct a compact click feature. We represent each query as a click feature, and design a graph based propagation approach to predict the zero-clicks, ensuring similar images have similar clicks. Afterwards, using this feature, we formulate the problem as a sparse coding based recognition task, wherein the dictionary is discriminatively trained. We evaluate our method for fine-grained image recognition on the public Clickture-Dog dataset. It is shown that, the propagated click feature performs much better than the original one. Also, sparse coding performs better than K-means in query merging. © Springer Nature Singapore Pte Ltd. 2018.

关键词： Image recognition

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Machine Learning Security Analysis Framework Based on Threat Matrix 8

Machine Learning Security Analysis Framework Based on Threat...

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8th International Conference on Data science in Cyberspace, DSC 2023

作者： Li, Hu Ma, Qiongmin Zhang, Ming Kuang, Xiaohui National Key Laboratory of Science and Technology on Information System Security Beijing China National Key Laboratory for Complex Systems Simulation Beijing China

ISBN: (纸本)9798350331035

Machine Learning and Artificial Intelligence technology accelerates technological progress and promotes social development, but also brings many security problems. Machine learning models may be affected, deceived, controlled or destroyed at different stages, e.g. training and inference, which may lead to serious consequences. In view of the main stages of the life cycle of machine learning, we summarizes the related attack and defense technologies based on threat matrix, makes a comprehensive and systematic analysis on the security issues of machine learning, and puts forward several security protection suggestions for intelligent information systems. © 2023 IEEE.

关键词： Artificial Intelligence Machine Learning Security Analysis Threat Matrix

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Radar Signal Detection Based on Ambiguity Function and Deep Learning 2

Radar Signal Detection Based on Ambiguity Function and Deep ...

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2nd International Conference on Computer Engineering and Application, ICCEA 2021

作者： Lv, Fengrong Dong, Zeyu Wan, Tao Jiang, Kaili Fang, Xueli Zhang, Lei University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu China Key Laboratory of Complex Aviation Simulation System Beijing China

ISBN: (纸本)9781665426169

The ambiguity function describes the joint characteristics of the signal in the time domain and the frequency domain, and is usually used for signal recognition. The time domain and frequency domain distribution of noise is more spurious than the signal. Its ambiguity function can also reflect its characteristics. However, the direct use of the ambiguity function as the signal feature will increase the amount of calculation of the detection system, so slice it, which reduces the burden on the system for detecting signal information while preserving the information. At the same time, the radar signal detection based on neural network can avoid the influence of artificially setting the threshold on the detection performance of the system. So, we propose an algorithm for inputting the extracted fuzzy function slice sequence into a neural network to realize signal detection. simulation proves that when the signal-To-noise ratio of the received signal is very low, our proposed method still has a high detection probability. © 2021 IEEE.

关键词： Signal detection

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Semi-supervised Open-set Recognition of Radar Active Jamming

Semi-supervised Open-set Recognition of Radar Active Jamming

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2021 CIE International Conference on Radar, Radar 2021

作者： Li, Hao Fang, Xueli Zhang, Lei Kang, Hui Zhang, Wei School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu China Key Laboratory of Complex Aviation Simulation System Beijing China

ISBN: (纸本)9781665498142

With the emergence of various kinds of complex radar jamming, radar jamming intelligent recognition technology has increasingly become the key to electronic counter-counter measures. To achieve radar jamming open-set recognition with a small number of tagged samples, Generative adversarial network-based pseudolabeled convolutional neural network (GAN-PL-CNN) model is proposed in this paper. Firstly, radar jamming is modelled, and the radar jamming datasets with known and unknown types are established after time-frequency transformation and image processing. Then, the adaptive pseudolabeling method is used to achieve semi-supervised recognition of radar jamming by combining the learning capability of convolutional neural networks and the characteristics of pseudolabeling to increase labeled samples intelligently. Finally, generative adversarial networks are introduced to enhance the recognition ability of the model and the discrimination ability of the unknown type through the game between the generator and the discriminator in the iterative process. Experimental results show that the GAN-PL-CNN model achieves 89.7%-95.1% for known types and 30.7%-86.8% for unknown types at 3%-6% labeling rate. As the number of labeled samples increases, the recognition effect becomes better and has a greater ability to exclude unknown type. © 2021 IEEE.

关键词： convolutional neural network open-set recognition pseudo-label Radar active jamming

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