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Cognitive interference decision method for air defense missile fuze based on reinforcement learning

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Defence Technology（防务技术） 2024年第2期32卷 393-404页

作者： Dingkun Huang Xiaopeng yan Jian Dai Xinwei Wang yangtian liu Science and Technology on Electromechanical Dynamic Control Laboratory School of Mechatronical EngineeringBeijing Institute of TechnologyBeijing 100081China

To solve the problem of the low interference success rate of air defense missile radio fuzes due to the unified interference form of the traditional fuze interference system,an interference decision method based Q-learning algorithm is ***,dividing the distance between the missile and the target into multiple states to increase the quantity of state ***,a multidimensional motion space is utilized,and the search range of which changes with the distance of the projectile,to select parameters and minimize the amount of ineffective interference *** interference effect is determined by detecting whether the fuze signal ***,a weighted reward function is used to determine the reward value based on the range state,output power,and parameter quantity information of the interference *** effectiveness of the proposed method in selecting the range of motion space parameters and designing the discrimination degree of the reward function has been verified through offline experiments involving full-range missile *** optimal interference form for each distance state has been *** with the single-interference decision method,the proposed decision method can effectively improve the success rate of interference.

关键词： Cognitive radio Interference decision Radio fuze Reinforcement learning Interference strategy optimization

IoV environment exploring coordination:A federated learning approach

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Digital Communications and Networks 2024年第1期10卷 135-141页

作者： Tong Ding Lei liu Yi Zhu Lizhen Cui Zhongmin yan School of Software Shandong UniversityJinan250101China

Exploring open fields with coordinated unmanned vehicles is popular in academia and *** of the most impressive applicable approaches is the Internet of Vehicles(lov).The IoV connects vehicles,road infrastructures and communication facilities to provide solutions for exploration ***,the coordination of acquiring information from multi-vehicles may risk data *** this end,sharing high-quality experiences instead of raw data has become an urgent *** paper employs a Deep Reinforcement Learning(DRL)method to enable IoVs to generate training data with prioritized experience and states,which can support the IoV to explore the environment more ***,a Federated Learning(FL)experience sharing model is established to guarantee the vehicles'*** numerical results show that the proposed method presents a better successful sharing rate and a more stable convergence within the comparison of fundamental *** experiments also suggest that the proposed method could support agents without full information to achieve the tasks.

关键词： Internet of vehicle Deep reinforcement learning Federated learning Data privacy

A survey of energy-efficient strategies for federated learning in mobile edge computing

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Frontiers of Information Technology & Electronic Engineering 2024年第5期25卷 645-663页

作者： Kang yan Nina SHU Tao WU Chunsheng liu Panlong yanG School of Electronic Engineering National University of Defense TechnologyHefei 230009China Department of Computing Hong Kong Polytechnic UniversityHong Kong 999077China School of Computer Science and Technology University of Science and Technology of ChinaHefei 230026China

With the booming development of fifth-generation network technology and Internet of Things,the number of end-user devices(EDs)and diverse applications is surging,resulting in massive data generated at the edge of *** process these data eficiently,the innovative mobile edge computing(MEC)framework has emerged to guarantee low latency and enable eficient computing close to the user ***,federated learning(FL)has demonstrated its empirical success in edge computing due to its privacy-preserving ***,it becomes a promising solution for analyzing and processing distributed data on EDs in various machine learning tasks,which are the major workloads in ***,EDs are typically powered by batteries with limited capacity,which brings challenges when performing energy-intensive FL *** address these challenges,many strategies have been proposed to save energy in *** the absence of a survey that thoroughly summarizes and classifies these strategies,in this paper,we provide a comprehensive survey of recent advances in energy-efficient strategies for FL in ***,we first introduce the system model and energy consumption models in FL,in terms of computation and *** we analyze the challenges regarding improving energy efficiency and summarize the energy-efficient strategies from three perspectives:learning-based,resource allocation,and client *** conduct a detailed analysis of these strategies,comparing their advantages and ***,we visually illustrate the impact of these strategies on the performance of FL by showcasing experimental ***,several potential future research directions for energy-efficient FL are discussed.

关键词： Mobile edge computing Federated learning Energy-efficient

Real-Time Co-optimization of Gear Shifting and Engine Torque for Predictive Cruise Control of Heavy-Duty Trucks

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Chinese Journal of Mechanical Engineering 2024年第2期37卷 294-317页

作者： Hongqing Chu Xiaoxiang na Huan liu Yuhai Wang Zhuo yang Lin Zhang Hong Chen School of Automotive Studies Tongji UniversityShanghaiChina Department of Engineering University of CambridgeCambridgeUK State Key Laboratory of Automotive Simulation and Control Jilin UniversityChangchunChina Qingdao Automotive Research Institute Jilin UniversityQingdaoChina Dongfeng Commercial Vehicle Technology Center Dongfeng Motor CorporationWuhanChina

Fuel consumption is one of the main concerns for heavy-duty *** cruise control(PCC)provides an intriguing opportunity to reduce fuel consumption by using the upcoming road *** this study,a real-time implementable PCC,which simultaneously optimizes engine torque and gear shifting,is proposed for heavy-duty *** minimize fuel consumption,the problem of the PCC is formulated as a nonlinear model predictive control(MPC),in which the upcoming road elevation information is *** the solution of the nonlinear MPC is time consuming;thus,a real-time implementable solver is developed based on Pontryagin’s maximum principle and indirect shooting *** programming(DP)algorithm,as a global optimization algorithm,is used as a performance benchmark for the proposed ***,hardware-in-the-loop and real-truck experiments are conducted to verify the performance of the proposed *** results demonstrate that the MPC-based solution performs nearly as well as the DP-based solution,with less than 1%deviation for testing ***,the proposed co-optimization controller is implementable in a real-truck,and the proposed MPC-based PCC algorithm achieves a fuel-saving rate of 7.9%without compromising the truck’s travel time.

关键词： Heavy-duty truck Predictive cruise control Model predictive control Pontryagin’s maximum principle Real-truck implementation

Giant low-field reversible magnetocaloric effect at liquid helium temperature of niobium and iron co-substituted EuTiO_(3) compounds

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Journal of Rare Earths 2024年第4期42卷 710-715页

作者： Zhihong Hao Quanyi liu Huicai Xie yan Zhang Zhaojun Mo School of Rare Earth and New Materials Engineering Ganzhou Innovation Center of Rare Earth Permanent Magnet Material Advanced Manufacturing and Intelligent Equipment TechnologyGannan University of Science and TechnologyGanzhou341000China Ganjiang Innovation Academy Chinese Academy of SciencesGanzhou34119China School of Materials Science and Engineering Taiyuan University of Science and TechnologyTaiyuan030024China

Giant magnetocaloric effect(MCE)materials in the liquid helium temperature region have attracted a lot of attention in the field of low-temperature magnetic refrigeration(MR).In this study,a series of niobium(Nb)and iron(Fe)co-substituted EuTiO_(3) perovskites with cubic structure(space group pm3m)was successfully fabricated,and their magnetic properties as well as cryogenic magnetocaloric effects were investigated in *** expected,the introduction of Nb and Fe can significantly modulate the magnetic phase transition and magnetocaloric effect of the EuTiO_(3) *** increasing Fe concentration,two local minima corresponding to the AFM-FM magnetic phase transition near 5.0 K and FM-PM transition near 10 K with no hysteresis in the thermomagnetic curves are observed,which is attributed to an enhancement of FM *** the same time,the gradually widened-ΔSM-T curves and the two peaks with a broad shoulder lead to considerable refrigeration capacity(RC).With the field change ofΔH=2 T,the calculated values of-ΔS_(M)^(max) for the EuTi_(0.9375-x)Nb_(0.0625)Fe_(x)O_(3)(x=0.075,0.1,0.125,0.15)compounds are 24.2,17.6,14.5 and 14.0 J/(kg·K),*** corresponding RC values were calculated to be 144.6,138.3,151.2 and 159 J/kg,***,the values of-ΔS_(M)^(max) for EuTi_(0.8625)Nb_(0.0625)Fe_(0.075)O_(3) are 8.6 and 15.1 J/(kg·K)under low field changes of 0.5 and 1 T,*** giant low-field reversible magnetocaloric effect makes them attractive candidates for magnetic refrigeration in the liquid helium temperature region.

关键词： Magnetocaloric effect Refrigeration capacity Magnetic entropy change Rareearths

Comparison of Rotating Stall Warning by Different Methods for Variable Speed Configurations in a Contra-Rotating Compressor

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Journal of Thermal Science 2024年第4期33卷 1379-1393页

作者： XUE Fei WANG yan'gang liu Qian WU Tong liu Hanru School of Power and Energy Northwestern Polytechnical UniversityXi’an710072China

Stall in compressors can cause performance degradation and even lead to *** unacceptable consequences can be avoided by timely monitoring stall inception and taking effective *** paper focused on the rotating stall warning in a low-speed axial contra-rotating ***,the stall disturbance characteristics under different speed configurations were *** results showed that as the speed ratio(RR)increased,the stall disturbance propagation speed based on the rear rotor speed gradually ***,the standard deviation(SD)method,the cross-correlation(CC)method,and the discrete wavelet transform(DWT)method were employed to obtain the stall initiation moments of three different speed *** was found that the SD and CC methods did not achieve significant stall warning results in all three speed ***,the stall initiation moment obtained by the DWT method at RR=1.125 was one period after the stall had fully developed,which was ***,a stall warning method was developed in the present work based on the long short-term memory(LSTM)regression *** applying the LSTM model,the predicted stall initiation moments of three speed configurations were at the 557th,518th,and 333rd revolution,which were44,2,and 74 revolutions ahead of stall onset moments,***,in scenarios where a minor disturbance preceded the stall,the stall warning effect of the LSTM was greatly improved in comparison with the aforementioned three *** contrast,when the pressure fluctuation before the stall was relatively small,the differences between the stall initiation moments predicted by these four methods were not significant.

关键词： contra-rotating compressor stall disturbance stall initiation moment long short-term memory(LSTM) stall warning

Multi-Scale Feature Fusion Model for Bridge Appearance Defect Detection

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Big Data Mining and Analytics 2024年第1期7卷 1-11页

作者： Rong Pang yan yang Aiguo Huang yan liu Peng Zhang Guangwu Tang School of Computing and Artificial Intelligence Southwest Jiaotong UniversityChengdu 611756China China Merchants Chongqing Road Engineering Inspection Center Co. Ltd.Chongqing 400067China State Key Laboratory of Bridge Engineering Structural Dynamics Chongqing 400067China

Although the Faster Region-based Convolutional Neural Network(Faster R-CNN)model has obvious advantages in defect recognition,it still cannot overcome challenging problems,such as time-consuming,small targets,irregular shapes,and strong noise interference in bridge defect *** deal with these issues,this paper proposes a novel Multi-scale Feature Fusion(MFF)model for bridge appearance disease ***,the Faster R-CNN model adopts Region Of Interest(ROl)pooling,which omits the edge information of the target area,resulting in some missed detections and inaccuracies in both detecting and localizing bridge ***,this paper proposes an MFF based on regional feature Aggregation(MFF-A),which reduces the missed detection rate of bridge defect detection and improves the positioning accuracy of the target ***,the Faster R-CNN model is insensitive to small targets,irregular shapes,and strong noises in bridge defect detection,which results in a long training time and low recognition ***,a novel Lightweight MFF(namely MFF-L)model for bridge appearance defect detection using a lightweight network EfficientNetV2 and a feature pyramid network is proposed,which fuses multi-scale features to shorten the training speed and improve recognition ***,the effectiveness of the proposed method is evaluated on the bridge disease dataset and public computational fluid dynamic dataset.

关键词： defect detection Multi-scale Feature Fusion(MFF) Region Of Interest(ROl)alignment lightweight network

Failure evaluation and control factor analysis of slope block instability along traffic corridor in Southeastern Tibet

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Journal of Mountain Science 2024年第6期21卷 1830-1848页

作者： liu Changqing BAO Han LAN Hengxing yan Changgen LI Changbo liu Shijie School of Highway Chang'an UniversityXi'an 710064China State Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing 100101China College of Geological Engineering and Geomatics Chang'an UniversityXi'an 710054China

The instability of slope blocks occurred frequently along traffic corridor in Southeastern Tibet(TCST),which was primarily controlled by the rock mass structures.A rapid method evaluating the control effects of rock mass structures was proposed through field statistics of the slopes and rock mass structures along TCST,which combined the stereographic projection method,modified M-JCS model,and limit equilibrium *** instabilities of slope blocks along TCST were then evaluated rapidly,and the different control factors of instability were *** showed that the probabilities of toppling(5.31%),planar(16.15%),and wedge(35.37%)failure of slope blocks along TCST increased *** instability modes were respectively controlled by the anti-dip joint,the joint parallel to slope surface with a dip angle smaller than the slope angle(singlejoint),and two groups of joints inclined out of the slope(double-joints).Regarding the control effects on slope block instability,the stabilization ability of doublejoints(72.7%),anti-dip joint(67.4%),and single-joint(57.6%)decreased sequentially,resulting in different probabilities of slope block ***,nearby regional faults significantly influenced the joints,leading to spatial heterogeneity and segmental clustering in the stabilization ability provided by joints to the slope ***,the stability of slope blocks gradually weakened as they approached the fault *** paper can provide guidance and assistance for investigating the development characteristics of rock mass structures and the stability of slope blocks.

关键词： Slope engineering Block instability Rapid evaluation method Rock mass structure Control factor

Microstructure Features and the Macroscopic Acoustic Behavior of Gassy Silt in the Yellow River Delta

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Journal of Ocean University of China 2024年第2期23卷 371-382页

作者： liu Tao GUO Zhenqi ZHANG yan WU Chen liu Lele DENG Shenggui Laboratory for Marine Geology Pilot National Laboratory for Marine Science and TechnologyQingdao 266061China Shandong Provincial Key Laboratory of Marine Environment and Geological Engineering Ocean University of ChinaQingdao 266100China College of Civil Engineering Anhui Jianzhu UniversityHefei 230601China The Key Laboratory of Gas Hydrate Ministry of Natural ResourcesQingdao Institute of Marine GeologyQingdao 266071China College of Marine Geosciences Key Laboratory of Submarine Geosciences and ProspectingOcean University of ChinaQingdao 266100China

The morphological changes in isolated bubbles in gassy silt play a critical role in the microscopic structures between soil particles and bubbles and macroscopic physical *** on X-ray CT scanning experiments under various vertical loads(four levels),self-designed acoustic macro experiments,and a series of formula revisions to the macro-air-bearing silt sound-velocity prediction model,this paper discusses the macro-and micro-scale features of gassy silts from the Yellow River *** samples consisted of different proportions of silt from the Yellow River Delta and porous media,and they were used to form two types of aerosol silts with initial gas contents of 4.23%and 7.67%.The results show that the air bubble content and external load considerably affect the microstructural parameters and acoustic behavior of gassy silt in the Yellow River *** macroscopic sound velocity showed a linear positive correlation with vertical load and relation to microstructural parameters in varying manners and *** on the traditional Biot-Stoll acoustic model,the gas-phase medium coefficient was introduced for the proper calculation and prediction of the sound velocity of air-bearing *** errors of the overall prediction varied between 5.6%and 9.6%.

关键词： gassy silt vertical load microstructure parameters bubble vibration Biot-Stoll acoustic model