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5th International Conference on Pattern Recognition and Artificial Intelligence, PRAI 2022

作者： Liu, Wenqiang Li, Yang Wang, Jiabao Miao, Zhuang Qiu, Hangping Army Engineering University of Pla Command & Control Engineering College Nanjing210007 China

ISBN: (数字)9781665499163

ISBN: (纸本)9781665499163

Multi-Object Tracking (MOT) has achieved tremendous progress in the past few years. However, almost all existing joint detection and embedding (JDE) based methods have overlooked the ground-truth annotation qualities affect by occlusion. In this paper, we argue that MOT annotations are often effect by noisy labels. In addition, these noisy labels are actually harmful for the training process of JDE based method. To address this challenge, we propose a novel Multi-Object Tracking method for Noisy Labels, named MOTNL. MOTNL can not only diagnose noisy labels but also choose more high-quality clean labels for model training. Specifically, we first analyze the properties of occluded samples in multi-object tracking video datasets. And design a simple but effective selection mechanism in the Re-ID branch of our MOTNL. Extensive results on different baseline show that training with carefully selected samples leads to significant improvements for different MOT methods. © 2022 IEEE.

关键词： Computer vision

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Evolution Mechanism of Unmanned Cluster Cooperation Oriented Toward Strategy Selection Diversity

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Journal of Systems engineering and Electronics 2025年第2期36卷 462-482页

作者： Xie Zhenhai Yu Minggang He Ming Chen Guoyou Zhai Zheng Wang Ziyu Liu Lu Institute of Command and Control Engineering Army Engineering University of PLA Nanjing China Unit 31630 of the Chinese People's Liberation Army Huizhou China

When performing tasks, unmanned clusters often face a variety of strategy choices. One of the key issues in unmanned cluster tasks is the method through which to design autonomous collaboration and cooperative evolution mechanisms that allow for unmanned clusters to maximize their overall task effectiveness under the condition of strategic diversity. This paper analyzes these task requirements from three perspectives: the diversity of the decision space, information network construction, and the autonomous collaboration mechanism. Then, this paper proposes a method for solving the problem of strategy selection diversity under two network structures. Next, this paper presents a Moran-rule-based evolution dynamics model for unmanned cluster strategies and a vision-driven-mechanism-based evolution dynamics model for unmanned cluster strategy in the context of strategy selection diversity according to various unmanned cluster application scenarios. Finally, this paper provides a simulation analysis of the effects of relevant parameters such as the payoff factor and cluster size on cooperative evolution in autonomous cluster collaboration for the two types of models. On this basis, this paper presents advice for effectively addressing diverse choices in unmanned cluster tasks, thereby providing decision support for practical applications of unmanned cluster tasks.

关键词： Games Collaboration Modeling Stochastic processes Information processing Heuristic algorithms Complex networks Investment Hands Decision making

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Multi-influenced Factors Prediction Using a Combination of GEP and PCA-GRNN Model Based on the Shapley Value Method

Multi-influenced Factors Prediction Using a Combination of G...

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2022 International Conference on Artificial Intelligence, Information Processing and Cloud Computing, AIIPCC 2022

作者： Xia, Chenxi Dai, Wanlu Li, Dong Li, Fengling Liu, Kai He, Zhijie Unit 31680 of PLA Chengdu China Command and Control Engineering College the Army Engineering University of PLA Nanjing China

ISBN: (纸本)9781665462877

The powerful function mining ability of the gene expression programming algorithm has obvious advantages in predicting dependent variables under multi-influence factors. PCA can obtain the key characteristics of the main influencing factors by the data reduction processing, and the generalized regression neural network can effectively overcome the disadvantage of slow training of the traditional neural network. Taking the cost of civil engineering in subway tunnels as an example, this paper introduces the Shapley value method for a combined prediction based on the prediction results of the above two optimal single prediction models and determines the weight of the two models based on the error of allocation. The results of the study show that the combined prediction model based on the Shapley value method reduces the error better than the single prediction model and further improves the prediction accuracy. © 2022 IEEE.

关键词： Principal component analysis

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Fractal evaluation model based on fractal dimension and its applications in reinforcement learning

Fractal evaluation model based on fractal dimension and its ...

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第35届中国控制与决策会议

作者： Li Yuan Wang Jun Li Ge Zhang Ren Wen Sun Rui Jin Army Engineering University of PLA Command Control Engineering Institute

Game reinforcement learning has many inherent difficulties in the research process,such as the existence of pure strategy Nash equilibrium,the slow convergence speed of the algorithms,and the uncertainty in reinforcement learning *** characterization of the uncertainty will determine the scientificity and rationality of the *** test of the generality of the algorithms is mainly reflected in whether the algorithm can solve discrete problems and continuous *** main idea of the evaluation model based on fractal dimension is that the agent's strategy selection is aimed at maximizing the fractal dimension of the current *** fractal dimension at this time can be a set or a function and the above two cases correspond to discrete and continuous *** the discussion of Lyapuno stability theory,it can be concluded that the larger the fractal dimension,the more stable the state.

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An executable modeling and analyzing approach to C4ISR architecture

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Journal of Systems engineering and Electronics 2020年第1期31卷 109-117页

作者： HE Hongyue ZHU Weixing LI Ruiyang DENG Qiaoyu Institute of Command and Control Engineering Army Engineering University of PLA

To analyze the behavioral model of the command,control,communication,computer,intelligence,surveillance,reconnaissance(C4ISR)architecture,we propose an executable modeling and analyzing approach to ***,the meta concept model of the C4ISR architecture is *** to the meta concept model,we construct the executable meta models of the C4ISR architecture by extending the meta models of ***,we define the concrete syntax and executable activity algebra(EAA)semantics for executable *** semantics functions are introduced to translating the syntax description of executable models into the item of *** support the execution of models,we propose the executable rules which are the structural operational semantics of ***,an area air defense of the C4ISR system is used to illustrate the feasibility of the approach.

关键词： command control communication computer intelligence surveillance reconnaissance(C4ISR)architecture meta model executable model algebraic semantics

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Monaural speech enhancement using U-net fused with multi-head self-attention

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Chinese Journal of Acoustics 2023年第1期42卷 98-118页

作者： FAN Junyi YANG Jibin ZHANG Xiongwei ZHENG Changyan Graduate School Army Engineering UniversityNanjing 210007 College of Command and Control Engineering Army Engineering UniversityNanjing 210007 Department of Test Control High-tech InstituteQingzhou 262500

Under low signal-to-noise ratio(SNR)and burst noise conditions,the speech enhancement effect of existing deep learning network models is not *** contrast,humans can exploit the long-term correlation of speech to form an integrated perception of different speech ***,describing the long-term dependencies of speech can help improve the enhancement performance under low SNR and burst noise *** by this feature,a time domain end-to-end monaural speech enhancement model TU-net that fuses the multi-head self-attention mechanism and U-net deep network is *** TU-net model adopts the codec layer structure of U-net to achieve multi-scale feature *** introduces the dual-path Transformer module using the multi-head self-attention mechanism to calculate the speech mask and better model long-term *** TU-net model is trained with a weighted sum loss function in the time,time-frequency,and perceptual *** experiments are carried out and the results show that with maintaining relatively fewer network model parameters,TU-net outperforms other similar monaural enhancement network models in several evaluation metrics such as perceptual evaluation of speech quality(PESQ),short-time objective intelligibility(STOI)and SNR gain under low SNR and burst noise conditions.

关键词： network speech noise

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Effect of Neutrinos on Angular Momentum of Dark Matter Halo

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Research in Astronomy and Astrophysics 2023年第8期23卷 355-363页

作者： Yu Chen Chang-Zhi Lu Yu Lu Tingting Zhang Tong-Jie Zhang Institute for Frontiers in Astronomy and Astrophysics Beijing Normal UniversityBeijing 102206China Department of Astronomy Beijing Normal UniversityBeijing 100875China Beijing Planetarium Beijing Academy of Science and TechnologyBeijing 100044China College of Command and Control Engineering PLA Army Engineering UniversityNanjing 210017China Institute for Astronomical Science Dezhou UniversityDezhou 253023China

Massive neutrinos are expected to affect the large-scale structure formation,including the major component of solid substances,dark matter *** halos are influenced by neutrinos is vital and interesting,and angular momentum(AM)as a significant feature provides a statistical perspective for this *** halos from TianNu N-body cosmological simulation with the co-evolving neutrino particles,we obtain some concrete ***,by comparing the same halos with and without neutrinos,in contrast to the neutrino-free case,over 89.71%of halos have smaller halo moduli,over 71.06%have smaller particle-mass-reduced(PMR)AM moduli,and over 95.44%change their orientations of less than 0°.***,the relative variation of PMR modulus is more visible for low-mass ***,to explore the PMR moduli of halos in dense or sparse areas,we divide the whole box into big cubes,and search for halos within a small spherical cell in a single *** the two-level divisions,we discover that in denser cubes,the variation of PMR moduli with massive neutrinos decreases more *** distinction suggests that neutrinos exert heavier influence on halos'moduli in compact *** massive neutrinos,most halos(86.60%)have lower masses than without neutrinos.

关键词： (cosmology:)dark matter-neutrinos-(cosmology:)large-scale structure of universe-methods data analysis

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A Novel Subcharacter-enhanced Hybrid Network for Chinese Text Classification

A Novel Subcharacter-enhanced Hybrid Network for Chinese Tex...

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Frontiers of Robotics and Software engineering (FRSE), International Conference on

作者： Lei Chen Yang Wang Yun Fei Zheng Zhen Yang Tieyong Cao Institute of Command-and-Control Engineering The Army Engineering University of PLA Nanjing China The Army Artillery and Denfense Academy of PLA Institute of Command-and-Control Engineering The Army Engineering University of PLA Nanjing China

Chinese text classification aimed to set pre-defined labels to given documents, and it is a very important research field. To deal with this problem, a novel subcharacter-enhanced hybrid network model called SHN is proposed. The proposed SHN can hierarchically extract the text semantic features. Firstly, our model decomposes Chinese words by Cangjie-code into subcharacters. Secondly, both word embeddings and subcharacters n-grams vectors are used as the input part of SHN, which is aimed to fuse both internal structure information and semantic information. Thirdly, SHN makes use of a bidirectional GRU module that contains word-level attention, to obtains semantic information from the sentences in document. Finally, a dynamic convolution neural network module is used by SHN, which aimed to extract high level features. Experiments carried out on two datasets show that SHN can obtain better results than conventional methods and is effective.

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Direction-of-Arrival Estimation Based on the Moving Array With/Without Model Mismatch

Direction-of-Arrival Estimation Based on the Moving Array Wi...

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IEEE Information Technology, Networking, Electronic and Automation control Conference

作者： Shaozhuang Wu Qiao Su Lu Bai Sihang Yang Chen Yang Zhiqing Ma College of Communications Engineering Army Engineering University of PLA College of Command and Control Engineering Army Engineering University of PLA Nanjing China

ISBN: (数字)9798350370805

ISBN: (纸本)9798350370812

This paper proposes the Direction-of-Arrival (DOA) estimation algorithms based on the moving array with and without model mismatch. Firstly, without model mismatch, dividing the uniform linear subarray extracted from the extended model based on the moving array into two parts, two selected receive signal vectors are obtained. By calculating the auto-covariance matrix and the cross-covariance matrix of these receive signal vectors, the DOAs can be estimated though eigenvalue decomposition. As for the model mismatch case, another receive signal vector can be gotten by introducing more delays, then, the DOAs can be obtained similarly with the proposed algorithm without model mismatch. Simulation results testify the effectiveness of the proposed algorithms, and provide the suggestions of the scope of application of two proposed algorithms.

关键词： Direction-of-arrival estimation Automation Computational modeling Simulation Estimation Vectors Eigenvalues and eigenfunctions Delays Matrix decomposition Information technology

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A Study on the Evaluation Method of Software Requirements Satisfaction Based on Multi-task Scene Flow 25

A Study on the Evaluation Method of Software Requirements Sa...

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Proceedings of the 4th International Conference on Computer, Artificial Intelligence and control engineering

作者： Ruiyang Li Weixing Zhu Min Gu Yunquan Xie Command and Control Engineering College of Army Engineering University of PLA Nanjing Jiangsu China

ISBN: (纸本)9798400712647

In the field of test and evaluation of weapon and equipment, capability Evaluation of military software is crucial to meet the mission requirements as much as possible. In order to improve the accuracy and reliability of the evaluation conclusion, a capability requirement satisfaction evaluation method, based on multi-task scenario flow and inspired by software scenario testing, is proposed in this paper. This method combines qualitative analysis with quantitative calculation. Firstly, it analyzes the typical mission scenarios and generates scenario flow diagram. Subsequently, it calculates capability importance scores according to the mapping between events and capability indicators. Then, it uses a capability requirement satisfaction function to calculate the capability value and analyzes the correlation between capability indicators based on the functional dependency network. Finally, the effectiveness of the method is verified by a case. The results show that this method can identify the shortcomings and constraints of the software capability, and expand software evaluation work from "quality assurance" to "capability assurance".

关键词： Capability Evaluation

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