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Constrained Networked Predictive Control for Nonlinear Systems Using a High-Order Fully Actuated System Approach 被引量:1
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作者 Yi Huang Guo-Ping Liu +1 位作者 Yi Yu Wenshan Hu 《IEEE/CAA Journal of Automatica Sinica》 2025年第2期478-480,共3页
Dear Editor,In this letter,a constrained networked predictive control strategy is proposed for the optimal control problem of complex nonlinear highorder fully actuated(HOFA)systems with noises.The method can effectiv... Dear Editor,In this letter,a constrained networked predictive control strategy is proposed for the optimal control problem of complex nonlinear highorder fully actuated(HOFA)systems with noises.The method can effectively deal with nonlinearities,constraints,and noises in the system,optimize the performance metric,and present an upper bound on the stable output of the system. 展开更多
关键词 optimal control problem constrained networked predictive control strategy Performance Optimization present upper bound Nonlinear Systems NOISES Constrained networked Predictive Control High Order Fully Actuated Systems
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Passenger travel behavior in urban rail transit based on the networked model
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作者 Haining Sun Keping Li +2 位作者 Zhiao Ma Yuanxi Xu Yan Liang 《Communications in Theoretical Physics》 2025年第12期1-13,共13页
Urban rail transit is an efficient and environmentally friendly mode of transport,which is an important means of transportation for passengers.From a holistic point of view,this paper constructs an urban rail transit ... Urban rail transit is an efficient and environmentally friendly mode of transport,which is an important means of transportation for passengers.From a holistic point of view,this paper constructs an urban rail transit interchange topology(URTIT)network based on the interchange relationships among lines.We investigate a unique influence propagation mechanism to explore the impact of applying new technologies on the passenger travel behavior of urban rail transit.We analyze the influence from three aspects:the influence range,the influence propagation path,and the influence intensity.Based on the Dijkstra algorithm,the influence propagation paths are found according to the shortest transfer time.The improved path-based gravity model is applied to measure the influence intensity.The case study on urban rail transit in Beijing,China is carried out.The influence propagation mechanism of a single line in the Beijing URTIT network is analyzed,considering that Beijing Subway Line S1 is equipped with magnetic levitation technology.We not only quantify the impact of technologies on passenger travel behavior of urban rail transit,but also perform the sensitivity analysis.To avoid randomness,the influence propagation mechanisms of all lines are explored in this paper.The research results correspond to the situation in reality,which can provide certain references for urban rail transit operation and planning. 展开更多
关键词 urban rail transit topology network influence propagation gravity model
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Optimal Secure Control of Networked Control Systems Under False Data Injection Attacks:A Multi-Stage Attack-Defense Game Approach
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作者 Dajun Du Yi Zhang +1 位作者 Baoyue Xu Minrui Fei 《IEEE/CAA Journal of Automatica Sinica》 2025年第4期821-823,共3页
Dear Editor,The attacker is always going to intrude covertly networked control systems(NCSs)by dynamically changing false data injection attacks(FDIAs)strategy,while the defender try their best to resist attacks by de... Dear Editor,The attacker is always going to intrude covertly networked control systems(NCSs)by dynamically changing false data injection attacks(FDIAs)strategy,while the defender try their best to resist attacks by designing defense strategy on the basis of identifying attack strategy,maintaining stable operation of NCSs.To solve this attack-defense game problem,this letter investigates optimal secure control of NCSs under FDIAs.First,for the alterations of energy caused by false data,a novel attack-defense game model is constructed,which considers the changes of energy caused by the actions of the defender and attacker in the forward and feedback channels. 展开更多
关键词 designing defense strategy networked control systems ncss alterations energy networked control systems false data injection attacks fdias strategywhile false data injection attacks optimal secure control identifying attack strategymaintaining
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Stackelberg game-based optimal secure control against hybrid attacks for networked control systems
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作者 Wei Xiong Yi Dong Liubin Zhou 《Journal of Automation and Intelligence》 2025年第3期236-241,共6页
This paper investigates the problem of optimal secure control for networked control systems under hybrid attacks.A control strategy based on the Stackelberg game framework is proposed,which differs from conventional m... This paper investigates the problem of optimal secure control for networked control systems under hybrid attacks.A control strategy based on the Stackelberg game framework is proposed,which differs from conventional methods by considering both denial-of-service(DoS)and false data injection(FDI)attacks simultaneously.Additionally,the stability conditions for the system under these hybrid attacks are established.It is technically challenging to design the control strategy by predicting attacker actions based on Stcakelberg game to ensure the system stability under hybrid attacks.Another technical difficulty lies in establishing the conditions for mean-square asymptotic stability due to the complexity of the attack scenarios Finally,simulations on an unstable batch reactor system under hybrid attacks demonstrate the effectiveness of the proposed strategy. 展开更多
关键词 Stackelberg game networked control systems Hybrid attacks DoS attack FDI attack
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Networked control with guaranteed performance for IoT rehabilitation robot under nonvanishing uncertainties and input quantization
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作者 Shilei Tan Xuesong Wang +1 位作者 Haoquan Zhou Wei Gong 《Digital Communications and Networks》 2025年第6期1774-1782,共9页
The Internet of Things(IoT)technology provides data acquisition,transmission,and analysis to control rehabilitation robots,encompassing sensor data from the robots as well as lidar signals for trajectory planning(desi... The Internet of Things(IoT)technology provides data acquisition,transmission,and analysis to control rehabilitation robots,encompassing sensor data from the robots as well as lidar signals for trajectory planning(desired trajectory).In IoT rehabilitation robot systems,managing nonvanishing uncertainties and input quantization is crucial for precise and reliable control performance.These challenges can cause instability and reduced effectiveness,particularly in adaptive networked control.This paper investigates networked control with guaranteed performance for IoT rehabilitation robots under nonvanishing uncertainties and input quantization.First,input quantization is managed via a quantization-aware control design,ensur stability and minimizing tracking errors,even with discrete control inputs,to avoid chattering.Second,the method handles nonvanishing uncertainties by adjusting control parameters via real-time neural network adaptation,maintaining consistent performance despite persistent disturbances.Third,the control scheme guarantees the desired tracking performance within a specified time,with all signals in the closed-loop system remaining uniformly bounded,offering a robust,reliable solution for IoT rehabilitation robot control.The simulation verifies the benefits and efficacy of the proposed control strategy. 展开更多
关键词 networked control IoT rehabilitation robot Guaranteed performance Nonvanishing uncertainties Input quantization
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Blockchain for transactive energy management in networked neighborhood microgrids
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作者 Zhikun Hu Mingyu Yan +2 位作者 Chongyu Wang Ahmed Alabdulwahab Mohammad Shahidehpour 《iEnergy》 2025年第4期235-246,共12页
The proliferation of distributed and renewable energy resources introduces additional operational challenges to power distribution systems.Transactive energy management,which allows networked neighborhood communities ... The proliferation of distributed and renewable energy resources introduces additional operational challenges to power distribution systems.Transactive energy management,which allows networked neighborhood communities and houses to trade energy,is expected to be developed as an effective method for accommodating additional uncertainties and security mandates pertaining to distributed energy resources.This paper proposes and analyzes a two-layer transactive energy market in which houses in networked neighborhood community microgrids will trade energy in respective market layers.This paper studies the blockchain applications to satisfy socioeconomic and technological concerns of secure transactive energy management in a two-level power distribution system.The numerical results for practical networked microgrids located at IllinoisTech−Bronzeville in Chicago illustrate the validity of the proposed blockchain-based transactive energy management for devising a distributed,scalable,efficient,and cybersecured power grid operation.The conclusion of the paper summarizes the prospects for blockchain applications to transactive energy management in power distribution systems. 展开更多
关键词 networked neighborhood microgrids blockchain system transactive energy management power distribution system distributed energy resources
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Impact of peer pressure on cooperation evolution in the networked prisoner’s dilemma game with migration mechanisms
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作者 Xianjia Wang Yanan Li Zhipeng Yang 《Chinese Physics B》 2025年第11期263-274,共12页
In social and ecological systems,individual migration behavior and peer pressure are crucial factors influencing decision-making and cooperative behavior.However,how migration regulates the evolution of cooperation an... In social and ecological systems,individual migration behavior and peer pressure are crucial factors influencing decision-making and cooperative behavior.However,how migration regulates the evolution of cooperation and the specific role of peer pressure in this process remain to be further investigated.To address this,this study develops a model that incorporates migration mechanisms and peer pressure within the framework of the networked prisoner’s dilemma game.Specifically,we modify the population structure and introduce a migration strategy based on payoff maximization,enabling individuals to dynamically adjust their positions according to the local environment.The model also considers the impact of peer pressure on individual decision-making and introduces heterogeneity in individuals’sensitivity to pressure,thereby systematically examining the role of both factors in the evolution of cooperative behavior.Based on this framework,we further compare our model with a scenario in which no migration mechanism is present to evaluate its impact on cooperative dynamics.The results reveal that the migration mechanism significantly promotes the evolution of cooperative behavior.Under this mechanism,higher individual sensitivity leads to an increased level of cooperation,and stronger peer pressure intensity more effectively enhances the promotion of cooperation.Additionally,the influence of population structure on cooperation frequency cannot be overlooked.An increase in vacant nodes provides cooperators with greater buffering space and more migration opportunities,making cooperative behavior more stable and facilitating its propagation within the system.These findings suggest that appropriately regulating individual mobility and reinforcing peer pressure constraints can enhance the stability and propagation of cooperative behavior,providing significant theoretical support for social governance,organizational management,and group collaboration. 展开更多
关键词 prisoner’s dilemma peer pressure migration mechanism COOPERATION two-dimensional grid network
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基于树形决策卷积神经网络的滚动轴承故障分层诊断
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作者 杨旭 吴程飞 +1 位作者 黄健 赵鹰昊 《北京工业大学学报》 北大核心 2026年第1期64-74,共11页
针对传统滚动轴承故障诊断中故障层次信息利用不充分、诊断精度不足的问题,提出一种带有树形决策层的卷积神经网络(convolutional neural network,CNN)方法以实现故障位置与严重程度的逐层诊断。该模型同时具备CNN的特征提取能力和决策... 针对传统滚动轴承故障诊断中故障层次信息利用不充分、诊断精度不足的问题,提出一种带有树形决策层的卷积神经网络(convolutional neural network,CNN)方法以实现故障位置与严重程度的逐层诊断。该模型同时具备CNN的特征提取能力和决策树的层次结构及分层决策特性。首先,采用共享网络层和2个任务特定的分支全连接层分别提取与故障位置和故障严重程度有关的特征;然后,将2个全连接层的分类结果输入到树形决策层,并使用加权层次分类损失调整模型权重参数,从而实现模型对故障层次信息的自学习;最后,应用帕德博恩大学轴承数据集进行算法性能测试。实验结果表明,该模型的平均分类准确率可达99.15%,与领域内其他的诊断模型相比,实现了更准确的故障位置和严重性的分类。 展开更多
关键词 故障诊断 分层诊断 滚动轴承 卷积神经网络(convolutional neural network CNN) 决策树 集成模型
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GPIO-Based Continuous Sliding Mode Control for Networked Control Systems Under Communication Delays With Experiments on Servo Motors
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作者 Kamal Rsetam Zhenwei Cao +1 位作者 Zhihong Man Xian-Ming Zhang 《IEEE/CAA Journal of Automatica Sinica》 2025年第1期99-113,共15页
To handle input and output time delays that commonly exist in many networked control systems(NCSs), a new robust continuous sliding mode control(CSMC) scheme is proposed for the output tracking in uncertain single inp... To handle input and output time delays that commonly exist in many networked control systems(NCSs), a new robust continuous sliding mode control(CSMC) scheme is proposed for the output tracking in uncertain single input-single-output(SISO) networked control systems. This scheme consists of three consecutive steps. First, although the network-induced delay in those systems can be effectively handled by using Pade approximation(PA), the unmatched disturbance cames out as another difficulty in the control design. Second, to actively estimate this unmatched disturbance, a generalized proportional integral observer(GPIO) technique is utilized based on only one measured state. Third, by constructing a new sliding manifold with the aid of the estimated unmatched disturbance and states, a GPIO-based CSMC is synthesized, which is employed to cope with not only matched and unmatched disturbances, but also networkinduced delays. The stability of the entire closed-loop system under the proposed GPIO-based CSMC is detailedly analyzed.The promising tracking efficiency and feasibility of the proposed control methodology are verified through simulations and experiments on Quanser's servo module for motion control under various test conditions. 展开更多
关键词 Continuous sliding mode control(CSMC) generalized proportional integral observer(GPIO) networked control systems(NCSs) pade approximation(PA) TIME-DELAY unsmatched disturbances
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Robust Predefined-Time Control for Optimal Formation of Networked Mobile Vehicle Systems
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作者 Jing-Zhe Xu Zhi-Wei Liu +2 位作者 Dingxin He Ming-Feng Ge Ming Chi 《IEEE/CAA Journal of Automatica Sinica》 2025年第4期824-826,共3页
Dear Editor,This letter addresses the robust predefined-time control challenge for leaderless optimal formation in networked mobile vehicle(NMV)systems.The aim is to minimize a composite global cost function derived f... Dear Editor,This letter addresses the robust predefined-time control challenge for leaderless optimal formation in networked mobile vehicle(NMV)systems.The aim is to minimize a composite global cost function derived from individual strongly convex functions of each agent,considering both input disturbances and network communication constraints.A novel predefined-time optimal formation control(PTOFC)algorithm is presented,ensuring agent state convergence to optimal formation positions within an adjustable settling time.Through the integration of an integral sliding mode technique,disturbances are effectively countered.A representative numerical example highlights the effectiveness and robustness of the developed approach. 展开更多
关键词 minimize composite global cost function integral sliding mode technique agent state convergence optimal formation networked mobile vehicle systems robust predefined time control strongly convex functions disturbances
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Distributed Cooperative Regulation for Networked Re-Entrant Manufacturing Systems
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作者 Chenguang Liu Qing Gao +1 位作者 Wei Wang Jinhu Lü 《IEEE/CAA Journal of Automatica Sinica》 2025年第3期636-638,共3页
Dear Editor,This letter focuses on the distributed cooperative regulation problem for a class of networked re-entrant manufacturing systems(RMSs).The networked system is structured with a three-tier architecture:the p... Dear Editor,This letter focuses on the distributed cooperative regulation problem for a class of networked re-entrant manufacturing systems(RMSs).The networked system is structured with a three-tier architecture:the production line,the manufacturing layer and the workshop layer.The dynamics of re-entrant production lines are governed by hyperbolic partial differential equations(PDEs)based on the law of mass conservation. 展开更多
关键词 production line networked re entrant manufacturing systems three tier architecture production linethe distributed cooperative regulation hyperbolic partial differential equations pdes based distributed cooperative regulation problem manufacturing layer
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基于渗流理论的城市交通网络与供水管网级联失效分析
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作者 胡群芳 张昱 +3 位作者 宋朝阳 赫磊 车德路 苏展 《同济大学学报(自然科学版)》 北大核心 2026年第1期31-39,共9页
为解决交通网络与供水管网之间耦合关系所引发各类突发事件级联失效作用及其建模量化问题,以上海市中心城区为案例,利用出租车GPS数据及道路、供水管网GIS(Geographic Information System)数据,通过空间匹配和时间属性融合建立动态耦合... 为解决交通网络与供水管网之间耦合关系所引发各类突发事件级联失效作用及其建模量化问题,以上海市中心城区为案例,利用出租车GPS数据及道路、供水管网GIS(Geographic Information System)数据,通过空间匹配和时间属性融合建立动态耦合网络,基于渗流理论提出网络影响力指数用于量化级联失效影响。结果表明,交通网络和供水管网之间存在显著的时空耦合效应,尤其在高峰时段供水管网的失效对交通网络的连通性和运行效率产生了直接影响。同时,通过构建解耦策略,提出管网规划和维护优化方案,可减少2个网络之间跨网络级联失效影响,可为提升城市关键基础设施韧性安全与运行可靠性提供参考。 展开更多
关键词 供水管网 交通网络 耦合网络 复杂网络 渗流理论 级联失效
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Joint Probabilistic Scheduling and Resource Allocation for Wireless Networked Control Systems
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作者 Meng Zheng Lei Zhang Wei Liang 《IEEE/CAA Journal of Automatica Sinica》 2025年第1期258-260,共3页
Dear Editor,This letter presents a joint probabilistic scheduling and resource allocation method(PSRA) for 5G-based wireless networked control systems(WNCSs). As a control-aware optimization method, PSRA minimizes the... Dear Editor,This letter presents a joint probabilistic scheduling and resource allocation method(PSRA) for 5G-based wireless networked control systems(WNCSs). As a control-aware optimization method, PSRA minimizes the linear quadratic Gaussian(LQG) control cost of WNCSs by optimizing the activation probability of subsystems, the number of uplink repetitions, and the durations of uplink and downlink phases. Simulation results show that PSRA achieves smaller LQG control costs than existing works. 展开更多
关键词 subsystem activation probability linear quadratic gaussian control cost number uplink repetitions wireless networked control systems joint probabilistic scheduling resource allocation method psra linear quadratic gaussian lqg G based activation probability subsystems
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极端天气下高速公路自洽能源系统应急资源优化调度方案
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作者 李艳波 张云锐 +4 位作者 杨凯 陈楚润 吕浩楠 武奇生 陈俊硕 《西安交通大学学报》 北大核心 2026年第1期190-200,共11页
针对近年来频发的极端天气灾害对高速公路交通及电力网络基础设施造成严重破坏,导致灾后应急资源调度困难的问题,提出了一种考虑交通网(TN)-电力网(PN)耦合网络的高速公路应急资源优化调度方案。分别搭建TN和PN模型以及TN-PN耦合网络模... 针对近年来频发的极端天气灾害对高速公路交通及电力网络基础设施造成严重破坏,导致灾后应急资源调度困难的问题,提出了一种考虑交通网(TN)-电力网(PN)耦合网络的高速公路应急资源优化调度方案。分别搭建TN和PN模型以及TN-PN耦合网络模型;结合历史气象数据构建极端天气模型并利用蒙特卡罗模拟抽样方法模拟故障场景,得到极端天气运行情况以及线路故障率曲线;利用Dijkstra算法分析应急资源移动路径并构建其调度模型,求出灾后最优调度路线;结合河南某高速公路自洽能源系统的相关数据进行灾后应急资源调度仿真。结果表明:所提优化调度方案比目前常用的两种方案能够提前1~2 h完成故障线路维修,故障负荷的平均负荷恢复量提高了5.95%和2.27%,恢复至正常运行状态所需时间缩短了31.38%和16.28%,可进一步提高应急资源调度效率和高速公路自洽能源系统弹性。 展开更多
关键词 自洽能源系统 极端天气 交通网-电力网耦合网络 应急资源调度
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基于多道卡尔曼滤波神经网络的无监督微地震去噪方法
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作者 张岩 张永雪 +4 位作者 魏子心 董宏丽 韩非 张林军 汪靖哲 《地球物理学报》 北大核心 2026年第1期353-365,共13页
微地震数据中有效信号的振幅、频率,及噪声具有显著的时变特征,当前微地震去噪方法中基于卡尔曼滤波方法高度依赖经验调参而影响应用效率,深度学习方法往往需要大量有效样本监督学习.针对以上问题,提出一种结合卡尔曼滤波与循环神经网... 微地震数据中有效信号的振幅、频率,及噪声具有显著的时变特征,当前微地震去噪方法中基于卡尔曼滤波方法高度依赖经验调参而影响应用效率,深度学习方法往往需要大量有效样本监督学习.针对以上问题,提出一种结合卡尔曼滤波与循环神经网络的无监督微地震数据去噪方法.首先,建立多道微地震数据的卡尔曼滤波状态预测与更新方程,充分利用多道相关性提高卡尔曼滤波参数的表征能力;其次,设计多道卡尔曼滤波状态预测与更新的RNN运算算子,通过链式梯度自动求取方式优化卡尔曼滤波的参数,构建基于循环神经网络模式的多道卡尔曼网络去噪;再次,结合无监督的微地震去噪训练方法,实现卡尔曼参数自动优化,避免有效数据标签的过度依赖;最后,通过理论正演与实际微地震数据的实验结果表明,本文方法在微地震去噪准确性与效率上优于传统卡尔曼滤波与变分自编码器等同类方法. 展开更多
关键词 微地震数据处理 卡尔曼滤波 循环神经网络 噪声压制 无监督网络
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基于轻量化SuperPoint网络的水下光学图像特征提取
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作者 刘艳 朱昌盛 +1 位作者 余彬 霍冠英 《河海大学学报(自然科学版)》 北大核心 2026年第1期167-176,共10页
针对水下光学图像质量下降导致的图像配准、三维重建等水下视觉任务中特征提取鲁棒性差的问题,提出了一种轻量化SuperPoint网络,该网络针对水下光学图像普遍存在颜色失真、模糊等细节退化问题,利用注意力机制,构建频域-空间域动态注意... 针对水下光学图像质量下降导致的图像配准、三维重建等水下视觉任务中特征提取鲁棒性差的问题,提出了一种轻量化SuperPoint网络,该网络针对水下光学图像普遍存在颜色失真、模糊等细节退化问题,利用注意力机制,构建频域-空间域动态注意力融合模块,融合频域与空间域的特征信息,提升网络在水下退化图像中的特征提取能力;构建残差特征增强深度可分离卷积模块,以降低模型复杂度并增强网络的特征提取能力。验证结果表明:该网络较SuperPoint网络参数量减少了13.8%,计算量降低了8.0%,帧率提升31.7%,光照变化和视角变化下的重复率分别提高了2.3%和2.1%,在SQUID和FLSea数据集上的特征点检测与匹配性能评估中具有较好的特征提取鲁棒性。 展开更多
关键词 水下光学图像 SuperPoint网络 轻量化网络 特征提取 特征融合
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基于Space P和K-means的货运航司航线网络特征分析研究
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作者 罗凤娥 卫昌波 +1 位作者 韩晓彤 郭玲玉 《现代电子技术》 北大核心 2026年第1期102-107,共6页
针对航空货运行业的迅速扩张,航空货运网络结构变得更加复杂,文中通过Space P建模方法构建了货运航空公司航线网络模型,并运用K-means聚类算法对网络进行了深入分析。选取度、平均路径长度、聚类系数和中间度等关键网络特性指标对航线... 针对航空货运行业的迅速扩张,航空货运网络结构变得更加复杂,文中通过Space P建模方法构建了货运航空公司航线网络模型,并运用K-means聚类算法对网络进行了深入分析。选取度、平均路径长度、聚类系数和中间度等关键网络特性指标对航线网络进行层次化分类,揭示了网络的复杂特征和层次结构。通过仿真实验评估了网络的小世界特性,并利用轮廓系数得到不同K值下的聚类结果,进而确定最优聚类结果。同时,模拟了航线网络在遭受攻击时的鲁棒性,实验结果表明:在航线网络较为脆弱的情况下,该方法为货运航司航线网络的优化和抗风险能力的提升提供了重要参考。 展开更多
关键词 航空货运 Space P 航线网络 复杂网络 聚类算法 网络特征
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胰高血糖素样肽1受体激动剂替西帕肽治疗阿尔茨海默病的潜在靶点
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作者 张晓敏 杜朋洋 +1 位作者 张秀萍 薛国芳 《中国组织工程研究》 北大核心 2026年第23期6122-6133,共12页
背景:胰高血糖素样肽1受体激动剂作为神经退行性疾病治疗的新型候选药物,已在阿尔茨海默病临床研究中取得突破性进展,其中索马鲁肽等药物已推进至Ⅲ期临床试验阶段。然而,目前对于该类药物神经保护效应的分子作用机制仍存在显著的知识... 背景:胰高血糖素样肽1受体激动剂作为神经退行性疾病治疗的新型候选药物,已在阿尔茨海默病临床研究中取得突破性进展,其中索马鲁肽等药物已推进至Ⅲ期临床试验阶段。然而,目前对于该类药物神经保护效应的分子作用机制仍存在显著的知识缺口。目的:创新性地整合多组学分析技术与网络药理学方法,系统解析阿尔茨海默病病理相关基因谱系与替西帕肽潜在作用靶点的交集网络,鉴定关键调控基因,并通过体内外实验验证其分子机制。方法:采用多维度研究策略:①基于DisGeNET数据库(整合了多种疾病相关的基因组学数据库)构建阿尔茨海默病差异表达基因谱。②通过PubChem数据库(小分子生物活性数据库)获取替西帕肽结构并筛选潜在靶点。③应用DAVID数据库开展GO功能注释及KEGG通路富集分析。④结合STRING数据库与Cytoscape 3.9.1构建蛋白质互作网络,经拓扑网络分析筛选关键基因。⑤细胞水平验证:将HT22细胞分为对照组、模型组(β-淀粉样蛋白1-42寡聚体处理36 h建立HT22细胞阿尔茨海默病体外模型)、给药组(先以β-淀粉样蛋白1-42寡聚体预处理24 h,再加入替西帕肽共处理12 h),通过Western blot分析血管紧张素Ⅱ2型受体蛋白表达,ELISA检测突触蛋白1、突触后致密物质95等突触功能标志物表达水平。⑥动物实验验证:实验分为3组,对照组为WT型C57BL/6小鼠,腹腔注射生理盐水;模型组为3xTg小鼠(拟阿尔茨海默症小鼠),腹腔注射生理盐水;给药组为3xTg小鼠,腹腔注射20 nmol/L替西帕肽;均为隔日1次,共给药15次。使用水迷宫技术分析阿尔茨海默病模型小鼠的认知行为学改善;使用Western blot定量分析β-淀粉样蛋白(6E10)、磷酸化的Tau蛋白(P-tau-181)的表达情况。结果与结论:①从DisGeNET数据库筛选出阿尔茨海默病相关联的基因,共得到3397个关联基因;根据蛋白关联度筛选出了10个连接度最高的关键基因:AGTR2、NTSR1、NTSR2、GHSR、C5AR1、C3AR1、OPRM1、SSTR2、OPRD1、STAT3;GO富集分析和KEGG通路分析,提示替西帕肽可能通过改善神经受体-配体功能来改善阿尔茨海默病。②细胞实验提示,替西帕肽可能通过改善阿尔茨海默病的突触功能来发挥治疗作用,血管紧张素Ⅱ2型受体可能是替西帕肽治疗阿尔茨海默病的潜在靶点。③动物实验提示,替西帕肽能够改善3xTg小鼠的认知能力,改善3xTg小鼠模型脑内的异常β-淀粉样蛋白沉积和Tau蛋白磷酸化。④结论:揭示血管紧张素Ⅱ2型受体是替西帕肽作用于阿尔茨海默病病理进程的关键分子靶点,替西帕肽可能通过调控血管紧张素Ⅱ2型受体介导的突触功能改善来治疗阿尔茨海默病。 展开更多
关键词 替西帕肽 阿尔茨海默病 网络药理学 血管紧张素Ⅱ2型受体 蛋白互作网络 突触功能
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基于CNN-LSTM方法的液环泵非稳态流场预测分析
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作者 张人会 唐玉 +1 位作者 郭广强 陈学炳 《农业机械学报》 北大核心 2026年第1期273-279,共7页
为实现对液环泵内非稳态气液两相流场的快速预测,提出了一种基于深度学习的非定常周期性流场预测方法,可以实现样本集之后未来一定时间段内流场的高精度快速预测。通过对液环泵非稳态CFD结果获取的各时间步上的流场快照建立流场数据集,... 为实现对液环泵内非稳态气液两相流场的快速预测,提出了一种基于深度学习的非定常周期性流场预测方法,可以实现样本集之后未来一定时间段内流场的高精度快速预测。通过对液环泵非稳态CFD结果获取的各时间步上的流场快照建立流场数据集,利用卷积神经网络(CNN)对流场快照进行特征提取,并结合长短期记忆神经网络(LSTM)构建时间序列神经网络预测模型,预测结果与CFD数值模拟结果进行对比,分析表明,CNN-LSTM模型能够实现对未来时刻非稳态流场的高精度预测;相态场、压力场、温度场的预测结果平均相对误差分别为1.37%、1.28%、1.78%;在利用LSTM预测壳体及进口压力脉动时,在样本集之后叶轮旋转360°时间上平均相对误差分别为1.61%、0.09%、0.20%。在样本空间外的预测集上,CNN-LSTM的预测性能优于本征正交分解(POD)方法,尽管在外延时间序列上的预测精度随时间增加逐渐下降,但在整个时间历程上保持了较好的预测精度,在预测内流场结果方面具有显著优势。 展开更多
关键词 液环泵 非稳态流场 卷积神经网络 长短期记忆神经网络
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融合生成扩散模型的不完全多模态情绪识别
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作者 马飞 王玉婷 +1 位作者 杨飞霞 徐光宪 《计算机科学与探索》 北大核心 2026年第1期206-216,共11页
人类多模态情绪识别将文本、视觉和声音等各种异构模态数据用于感知并理解人类情感。与单一模态相比,多模态数据中的互补信息有助于更稳健地理解情感。然而,在实际多模态场景中常存在不完全或缺失模态信息,严重阻碍对多模态特征的理解,... 人类多模态情绪识别将文本、视觉和声音等各种异构模态数据用于感知并理解人类情感。与单一模态相比,多模态数据中的互补信息有助于更稳健地理解情感。然而,在实际多模态场景中常存在不完全或缺失模态信息,严重阻碍对多模态特征的理解,从而导致情绪识别精度下降。针对以往的多模态情绪识别方法未能有效地处理模态在不完全或缺失情况下产生的识别精度下降的问题,提出了一种融合生成扩散模型的不完全多模态情绪识别方法,通过重构不完全模态数据信息,以提升情绪识别的精度。构建基于跨模态条件随机微分方程的生成扩散模型,在逆扩散过程中将可用模态信息通过可学习投影转化为漂移项的动态约束,生成不完全模态信息特征;构建不完全模态生成网络与融合重构模块的双向协同优化框架,利用联合目标函数实现生成质量与特征融合的梯度反向传播交互,通过分层注意力机制建立补全的不完全模态特征与真实特征的情感语义一致性约束。经过几组数据集测试结果表明,所提出的多模态情绪识别方法在多种不完全模态场景中取得了优越的情绪识别性能。 展开更多
关键词 多模态情绪识别 得分网络补全 融合重构
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