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Research on Euclidean Algorithm and Reection on Its Teaching
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作者 ZHANG Shaohua 《应用数学》 北大核心 2025年第1期308-310,共3页
In this paper,we prove that Euclid's algorithm,Bezout's equation and Divi-sion algorithm are equivalent to each other.Our result shows that Euclid has preliminarily established the theory of divisibility and t... In this paper,we prove that Euclid's algorithm,Bezout's equation and Divi-sion algorithm are equivalent to each other.Our result shows that Euclid has preliminarily established the theory of divisibility and the greatest common divisor.We further provided several suggestions for teaching. 展开更多
关键词 Euclid's algorithm Division algorithm Bezout's equation
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Fusion Algorithm Based on Improved A^(*)and DWA for USV Path Planning
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作者 Changyi Li Lei Yao Chao Mi 《哈尔滨工程大学学报(英文版)》 2025年第1期224-237,共14页
The traditional A^(*)algorithm exhibits a low efficiency in the path planning of unmanned surface vehicles(USVs).In addition,the path planned presents numerous redundant inflection waypoints,and the security is low,wh... The traditional A^(*)algorithm exhibits a low efficiency in the path planning of unmanned surface vehicles(USVs).In addition,the path planned presents numerous redundant inflection waypoints,and the security is low,which is not conducive to the control of USV and also affects navigation safety.In this paper,these problems were addressed through the following improvements.First,the path search angle and security were comprehensively considered,and a security expansion strategy of nodes based on the 5×5 neighborhood was proposed.The A^(*)algorithm search neighborhood was expanded from 3×3 to 5×5,and safe nodes were screened out for extension via the node security expansion strategy.This algorithm can also optimize path search angles while improving path security.Second,the distance from the current node to the target node was introduced into the heuristic function.The efficiency of the A^(*)algorithm was improved,and the path was smoothed using the Floyd algorithm.For the dynamic adjustment of the weight to improve the efficiency of DWA,the distance from the USV to the target point was introduced into the evaluation function of the dynamic-window approach(DWA)algorithm.Finally,combined with the local target point selection strategy,the optimized DWA algorithm was performed for local path planning.The experimental results show the smooth and safe path planned by the fusion algorithm,which can successfully avoid dynamic obstacles and is effective and feasible in path planning for USVs. 展开更多
关键词 Improved A^(*)algorithm Optimized DWA algorithm Unmanned surface vehicles Path planning Fusion algorithm
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Energy Efficient Clustering and Sink Mobility Protocol Using Hybrid Golden Jackal and Improved Whale Optimization Algorithm for Improving Network Longevity in WSNs
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作者 S B Lenin R Sugumar +2 位作者 J S Adeline Johnsana N Tamilarasan R Nathiya 《China Communications》 2025年第3期16-35,共20页
Reliable Cluster Head(CH)selectionbased routing protocols are necessary for increasing the packet transmission efficiency with optimal path discovery that never introduces degradation over the transmission reliability... Reliable Cluster Head(CH)selectionbased routing protocols are necessary for increasing the packet transmission efficiency with optimal path discovery that never introduces degradation over the transmission reliability.In this paper,Hybrid Golden Jackal,and Improved Whale Optimization Algorithm(HGJIWOA)is proposed as an effective and optimal routing protocol that guarantees efficient routing of data packets in the established between the CHs and the movable sink.This HGJIWOA included the phases of Dynamic Lens-Imaging Learning Strategy and Novel Update Rules for determining the reliable route essential for data packets broadcasting attained through fitness measure estimation-based CH selection.The process of CH selection achieved using Golden Jackal Optimization Algorithm(GJOA)completely depends on the factors of maintainability,consistency,trust,delay,and energy.The adopted GJOA algorithm play a dominant role in determining the optimal path of routing depending on the parameter of reduced delay and minimal distance.It further utilized Improved Whale Optimisation Algorithm(IWOA)for forwarding the data from chosen CHs to the BS via optimized route depending on the parameters of energy and distance.It also included a reliable route maintenance process that aids in deciding the selected route through which data need to be transmitted or re-routed.The simulation outcomes of the proposed HGJIWOA mechanism with different sensor nodes confirmed an improved mean throughput of 18.21%,sustained residual energy of 19.64%with minimized end-to-end delay of 21.82%,better than the competitive CH selection approaches. 展开更多
关键词 Cluster Heads(CHs) Golden Jackal Optimization algorithm(GJOA) Improved Whale Optimization algorithm(IWOA) unequal clustering
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DDoS Attack Tracking Using Multi-Round Iterative Viterbi Algorithm in Satellite Internet
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作者 Guo Wei Xu Jin +2 位作者 Pei Yukui Yin Liuguo Feng Wei 《China Communications》 2025年第3期148-163,共16页
Satellite Internet(SI)provides broadband access as a critical information infrastructure in 6G.However,with the integration of the terrestrial Internet,the influx of massive terrestrial traffic will bring significant ... Satellite Internet(SI)provides broadband access as a critical information infrastructure in 6G.However,with the integration of the terrestrial Internet,the influx of massive terrestrial traffic will bring significant threats to SI,among which DDoS attack will intensify the erosion of limited bandwidth resources.Therefore,this paper proposes a DDoS attack tracking scheme using a multi-round iterative Viterbi algorithm to achieve high-accuracy attack path reconstruction and fast internal source locking,protecting SI from the source.Firstly,to reduce communication overhead,the logarithmic representation of the traffic volume is added to the digests after modeling SI,generating the lightweight deviation degree to construct the observation probability matrix for the Viterbi algorithm.Secondly,the path node matrix is expanded to multi-index matrices in the Viterbi algorithm to store index information for all probability values,deriving the path with non-repeatability and maximum probability.Finally,multiple rounds of iterative Viterbi tracking are performed locally to track DDoS attack based on trimming tracking results.Simulation and experimental results show that the scheme can achieve 96.8%tracking accuracy of external and internal DDoS attack at 2.5 seconds,with the communication overhead at 268KB/s,effectively protecting the limited bandwidth resources of SI. 展开更多
关键词 DDoS tracking iterative Viterbi algorithm satellite Internet 6G
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Ship Path Planning Based on Sparse A^(*)Algorithm
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作者 Yongjian Zhai Jianhui Cui +3 位作者 Fanbin Meng Huawei Xie Chunyan Hou Bin Li 《哈尔滨工程大学学报(英文版)》 2025年第1期238-248,共11页
An improved version of the sparse A^(*)algorithm is proposed to address the common issue of excessive expansion of nodes and failure to consider current ship status and parameters in traditional path planning algorith... An improved version of the sparse A^(*)algorithm is proposed to address the common issue of excessive expansion of nodes and failure to consider current ship status and parameters in traditional path planning algorithms.This algorithm considers factors such as initial position and orientation of the ship,safety range,and ship draft to determine the optimal obstacle-avoiding route from the current to the destination point for ship planning.A coordinate transformation algorithm is also applied to convert commonly used latitude and longitude coordinates of ship travel paths to easily utilized and analyzed Cartesian coordinates.The algorithm incorporates a hierarchical chart processing algorithm to handle multilayered chart data.Furthermore,the algorithm considers the impact of ship length on grid size and density when implementing chart gridification,adjusting the grid size and density accordingly based on ship length.Simulation results show that compared to traditional path planning algorithms,the sparse A^(*)algorithm reduces the average number of path points by 25%,decreases the average maximum storage node number by 17%,and raises the average path turning angle by approximately 10°,effectively improving the safety of ship planning paths. 展开更多
关键词 Sparse A^(*)algorithm Path planning RASTERIZATION Coordinate transformation Image preprocessing
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An improved fluid flow algorithm for hydraulic fracturing:Optimizing domain volume and crack pressure update strategies
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作者 Wei Zhang Jing Bi +3 位作者 Yu Zhao Yongfa Zhang Chaolin Wang Yang Pan 《International Journal of Mining Science and Technology》 2025年第4期639-657,共19页
With the widespread adoption of hydraulic fracturing technology in oil and gas resource development,improving the accuracy and efficiency of fracturing simulations has become a critical research focus.This paper propo... With the widespread adoption of hydraulic fracturing technology in oil and gas resource development,improving the accuracy and efficiency of fracturing simulations has become a critical research focus.This paper proposes an improved fluid flow algorithm,aiming to enhance the computational efficiency of hydraulic fracturing simulations while ensuring computational accuracy.The algorithm optimizes the aperture law and iteration criteria,focusing on improving the domain volume and crack pressure update strategy,thereby enabling precise capture of dynamic borehole pressure variations during injection tests.The effectiveness of the algorithm is verified through three flow-solid coupling cases.The study also analyzes the effects of borehole size,domain volume,and crack pressure update strategy on fracturing behavior.Furthermore,the performance of the improved algorithm in terms of crack propagation rate,micro-crack formation,and fluid pressure distribution was further evaluated.The results indicate that while large-size boreholes delay crack initiation,the cracks propagate more rapidly once formed.Additionally,the optimized domain volume calculation and crack pressure update strategy significantly shorten the pressure propagation stage,promote crack propagation,and improve computational efficiency. 展开更多
关键词 Hydraulic fracturing Fluid flow algorithm Domain volume optimization Crack pressure update Borehole size
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Power forecasting method of ultra-short-term wind power cluster based on the convergence cross mapping algorithm
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作者 Yuzhe Yang Weiye Song +5 位作者 Shuang Han Jie Yan Han Wang Qiangsheng Dai Xuesong Huo Yongqian Liu 《Global Energy Interconnection》 2025年第1期28-42,共15页
The development of wind power clusters has scaled in terms of both scale and coverage,and the impact of weather fluctuations on cluster output changes has become increasingly complex.Accurately identifying the forward... The development of wind power clusters has scaled in terms of both scale and coverage,and the impact of weather fluctuations on cluster output changes has become increasingly complex.Accurately identifying the forward-looking information of key wind farms in a cluster under different weather conditions is an effective method to improve the accuracy of ultrashort-term cluster power forecasting.To this end,this paper proposes a refined modeling method for ultrashort-term wind power cluster forecasting based on a convergent cross-mapping algorithm.From the perspective of causality,key meteorological forecasting factors under different cluster power fluctuation processes were screened,and refined training modeling was performed for different fluctuation processes.First,a wind process description index system and classification model at the wind power cluster level are established to realize the classification of typical fluctuation processes.A meteorological-cluster power causal relationship evaluation model based on the convergent cross-mapping algorithm is pro-posed to screen meteorological forecasting factors under multiple types of typical fluctuation processes.Finally,a refined modeling meth-od for a variety of different typical fluctuation processes is proposed,and the strong causal meteorological forecasting factors of each scenario are used as inputs to realize high-precision modeling and forecasting of ultra-short-term wind cluster power.An example anal-ysis shows that the short-term wind power cluster power forecasting accuracy of the proposed method can reach 88.55%,which is 1.57-7.32%higher than that of traditional methods. 展开更多
关键词 Ultra-short-term wind power forecasting Wind power cluster Causality analysis Convergence cross mapping algorithm
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A novel heuristic pathfinding algorithm for 3D security modeling and vulnerability assessment
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作者 Jun Yang Yue-Ming Hong +2 位作者 Yu-Ming Lv Hao-Ming Ma Wen-Lin Wang 《Nuclear Science and Techniques》 2025年第5期152-166,共15页
Vulnerability assessment is a systematic process to identify security gaps in the design and evaluation of physical protection systems.Adversarial path planning is a widely used method for identifying potential vulner... Vulnerability assessment is a systematic process to identify security gaps in the design and evaluation of physical protection systems.Adversarial path planning is a widely used method for identifying potential vulnerabilities and threats to the security and resilience of critical infrastructures.However,achieving efficient path optimization in complex large-scale three-dimensional(3D)scenes remains a significant challenge for vulnerability assessment.This paper introduces a novel A^(*)-algorithmic framework for 3D security modeling and vulnerability assessment.Within this framework,the 3D facility models were first developed in 3ds Max and then incorporated into Unity for A^(*)heuristic pathfinding.The A^(*)-heuristic pathfinding algorithm was implemented with a geometric probability model to refine the detection and distance fields and achieve a rational approximation of the cost to reach the goal.An admissible heuristic is ensured by incorporating the minimum probability of detection(P_(D)^(min))and diagonal distance to estimate the heuristic function.The 3D A^(*)heuristic search was demonstrated using a hypothetical laboratory facility,where a comparison was also carried out between the A^(*)and Dijkstra algorithms for optimal path identification.Comparative results indicate that the proposed A^(*)-heuristic algorithm effectively identifies the most vulnerable adversarial pathfinding with high efficiency.Finally,the paper discusses hidden phenomena and open issues in efficient 3D pathfinding for security applications. 展开更多
关键词 Physical protection system 3D modeling and simulation Vulnerability assessment A^(*)Heuristic Pathfinding Dijkstra algorithm
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基于Sarsa算法的城轨列车节能控制策略研究 被引量:2
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作者 孟建军 蒋小一 +1 位作者 陈晓强 胥如迅 《铁道标准设计》 北大核心 2024年第8期8-14,共7页
针对城市轨道交通节能运行问题,提出一种基于Sarsa强化学习算法的城轨列车节能控制策略,实现了城轨列车在自动驾驶状态下,面对不同路况,执行减少能源消耗驾驶策略的同时兼顾准时性和舒适性。根据线路条件将列车状态进行离散化处理,将连... 针对城市轨道交通节能运行问题,提出一种基于Sarsa强化学习算法的城轨列车节能控制策略,实现了城轨列车在自动驾驶状态下,面对不同路况,执行减少能源消耗驾驶策略的同时兼顾准时性和舒适性。根据线路条件将列车状态进行离散化处理,将连续的驾驶过程分为若干个子区间进行分段求解。结合区间限速、初始状态、终末状态等限制条件,基于能耗及运行时间分别构造适当的奖励函数。同时,用当前状态下可达的最大速度与最小速度对可选速度集合进行限制,缩小探索空间,加快算法收敛。最后,通过对北京铁路亦庄线小红门站至肖村站的实例进行仿真。实验结果表明,与传统的动态规划方法相比,Sarsa算法在满足舒适性和准时性要求的情况下节能9.32%。相比于强化学习中的Q学习算法,在速度的选取过程中,超速次数也有明显下降。仿真结果证明Sarsa算法具有更好的节能效果和安全性。在算法参数不变的情况下,调整限速条件,与传统动态规划算法进行二次对比,依旧节能4.21%,验证了算法的鲁棒性。 展开更多
关键词 城市轨道交通 节能 强化学习 sarsa算法 控制策略
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基于改进Sarsa算法的拖轮动态调度方法
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作者 李佳琛 段兴锋 《重庆科技学院学报(自然科学版)》 CAS 2024年第3期42-48,共7页
从优化Sarsa算法的角度展开拖轮动态调度方法研究。采用强化学习框架并结合拖轮的状态和环境信息,建立状态-动作函数,进而搜索拖轮调度最佳策略。改进Sarsa算法中Q函数的更新方式,以克服收敛速度慢的问题。同时,根据学习率选择模式和动... 从优化Sarsa算法的角度展开拖轮动态调度方法研究。采用强化学习框架并结合拖轮的状态和环境信息,建立状态-动作函数,进而搜索拖轮调度最佳策略。改进Sarsa算法中Q函数的更新方式,以克服收敛速度慢的问题。同时,根据学习率选择模式和动作选择方式,对探索策略与利用策略加以平衡,以提高算法的收敛速度和性能。算例仿真实验结果表明,采用该算法可有效缩短船舶等待时间,进而提升拖轮资源的利用效率。 展开更多
关键词 sarsa算法 拖轮 自适应调度 强化学习 算法策略
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Underwater four-quadrant dual-beam circumferential scanning laser fuze using nonlinear adaptive backscatter filter based on pauseable SAF-LMS algorithm 被引量:2
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作者 Guangbo Xu Bingting Zha +2 位作者 Hailu Yuan Zhen Zheng He Zhang 《Defence Technology(防务技术)》 SCIE EI CAS CSCD 2024年第7期1-13,共13页
The phenomenon of a target echo peak overlapping with the backscattered echo peak significantly undermines the detection range and precision of underwater laser fuzes.To overcome this issue,we propose a four-quadrant ... The phenomenon of a target echo peak overlapping with the backscattered echo peak significantly undermines the detection range and precision of underwater laser fuzes.To overcome this issue,we propose a four-quadrant dual-beam circumferential scanning laser fuze to distinguish various interference signals and provide more real-time data for the backscatter filtering algorithm.This enhances the algorithm loading capability of the fuze.In order to address the problem of insufficient filtering capacity in existing linear backscatter filtering algorithms,we develop a nonlinear backscattering adaptive filter based on the spline adaptive filter least mean square(SAF-LMS)algorithm.We also designed an algorithm pause module to retain the original trend of the target echo peak,improving the time discrimination accuracy and anti-interference capability of the fuze.Finally,experiments are conducted with varying signal-to-noise ratios of the original underwater target echo signals.The experimental results show that the average signal-to-noise ratio before and after filtering can be improved by more than31 d B,with an increase of up to 76%in extreme detection distance. 展开更多
关键词 Laser fuze Underwater laser detection Backscatter adaptive filter Spline least mean square algorithm Nonlinear filtering algorithm
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A real-time intelligent lithology identification method based on a dynamic felling strategy weighted random forest algorithm 被引量:1
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作者 Tie Yan Rui Xu +2 位作者 Shi-Hui Sun Zhao-Kai Hou Jin-Yu Feng 《Petroleum Science》 SCIE EI CAS CSCD 2024年第2期1135-1148,共14页
Real-time intelligent lithology identification while drilling is vital to realizing downhole closed-loop drilling. The complex and changeable geological environment in the drilling makes lithology identification face ... Real-time intelligent lithology identification while drilling is vital to realizing downhole closed-loop drilling. The complex and changeable geological environment in the drilling makes lithology identification face many challenges. This paper studies the problems of difficult feature information extraction,low precision of thin-layer identification and limited applicability of the model in intelligent lithologic identification. The author tries to improve the comprehensive performance of the lithology identification model from three aspects: data feature extraction, class balance, and model design. A new real-time intelligent lithology identification model of dynamic felling strategy weighted random forest algorithm(DFW-RF) is proposed. According to the feature selection results, gamma ray and 2 MHz phase resistivity are the logging while drilling(LWD) parameters that significantly influence lithology identification. The comprehensive performance of the DFW-RF lithology identification model has been verified in the application of 3 wells in different areas. By comparing the prediction results of five typical lithology identification algorithms, the DFW-RF model has a higher lithology identification accuracy rate and F1 score. This model improves the identification accuracy of thin-layer lithology and is effective and feasible in different geological environments. The DFW-RF model plays a truly efficient role in the realtime intelligent identification of lithologic information in closed-loop drilling and has greater applicability, which is worthy of being widely used in logging interpretation. 展开更多
关键词 Intelligent drilling Closed-loop drilling Lithology identification Random forest algorithm Feature extraction
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Genetic algorithm assisted meta-atom design for high-performance metasurface optics 被引量:1
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作者 Zhenjie Yu Moxin Li +9 位作者 Zhenyu Xing Hao Gao Zeyang Liu Shiliang Pu Hui Mao Hong Cai Qiang Ma Wenqi Ren Jiang Zhu Cheng Zhang 《Opto-Electronic Science》 2024年第9期15-28,共14页
Metasurfaces,composed of planar arrays of intricately designed meta-atom structures,possess remarkable capabilities in controlling electromagnetic waves in various ways.A critical aspect of metasurface design involves... Metasurfaces,composed of planar arrays of intricately designed meta-atom structures,possess remarkable capabilities in controlling electromagnetic waves in various ways.A critical aspect of metasurface design involves selecting suitable meta-atoms to achieve target functionalities such as phase retardation,amplitude modulation,and polarization conversion.Conventional design processes often involve extensive parameter sweeping,a laborious and computationally intensive task heavily reliant on designer expertise and judgement.Here,we present an efficient genetic algorithm assisted meta-atom optimization method for high-performance metasurface optics,which is compatible to both single-and multiobjective device design tasks.We first employ the method for a single-objective design task and implement a high-efficiency Pancharatnam-Berry phase based metalens with an average focusing efficiency exceeding 80%in the visible spectrum.We then employ the method for a dual-objective metasurface design task and construct an efficient spin-multiplexed structural beam generator.The device is capable of generating zeroth-order and first-order Bessel beams respectively under right-handed and left-handed circular polarized illumination,with associated generation efficiencies surpassing 88%.Finally,we implement a wavelength and spin co-multiplexed four-channel metahologram capable of projecting two spin-multiplexed holographic images under each operational wavelength,with efficiencies over 50%.Our work offers a streamlined and easy-to-implement approach to meta-atom design and optimization,empowering designers to create diverse high-performance and multifunctional metasurface optics. 展开更多
关键词 metasurface metalens Bessel beam metahologram genetic algorithm
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Optimization of jamming formation of USV offboard active decoy clusters based on an improved PSO algorithm 被引量:1
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作者 Zhaodong Wu Yasong Luo Shengliang Hu 《Defence Technology(防务技术)》 SCIE EI CAS CSCD 2024年第2期529-540,共12页
Offboard active decoys(OADs)can effectively jam monopulse radars.However,for missiles approaching from a particular direction and distance,the OAD should be placed at a specific location,posing high requirements for t... Offboard active decoys(OADs)can effectively jam monopulse radars.However,for missiles approaching from a particular direction and distance,the OAD should be placed at a specific location,posing high requirements for timing and deployment.To improve the response speed and jamming effect,a cluster of OADs based on an unmanned surface vehicle(USV)is proposed.The formation of the cluster determines the effectiveness of jamming.First,based on the mechanism of OAD jamming,critical conditions are identified,and a method for assessing the jamming effect is proposed.Then,for the optimization of the cluster formation,a mathematical model is built,and a multi-tribe adaptive particle swarm optimization algorithm based on mutation strategy and Metropolis criterion(3M-APSO)is designed.Finally,the formation optimization problem is solved and analyzed using the 3M-APSO algorithm under specific scenarios.The results show that the improved algorithm has a faster convergence rate and superior performance as compared to the standard Adaptive-PSO algorithm.Compared with a single OAD,the optimal formation of USV-OAD cluster effectively fills the blind area and maximizes the use of jamming resources. 展开更多
关键词 Electronic countermeasure Offboard active decoy USV cluster Jamming formation optimization Improved PSO algorithm
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Identification of Lubricating Oil Additives Using XGBoost and Ant Colony Optimization Algorithms 被引量:1
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作者 Xia Yanqiu Cui Jinwei +2 位作者 Xie Peiyuan Zou Shaode Feng Xin 《China Petroleum Processing & Petrochemical Technology》 SCIE CAS CSCD 2024年第2期158-167,共10页
To address the problem of identifying multiple types of additives in lubricating oil,a method based on midinfrared spectral band selection using the eXtreme Gradient Boosting(XGBoost)algorithm combined with the ant co... To address the problem of identifying multiple types of additives in lubricating oil,a method based on midinfrared spectral band selection using the eXtreme Gradient Boosting(XGBoost)algorithm combined with the ant colony optimization(ACO)algorithm is proposed.The XGBoost algorithm was used to train and test three additives,T534(alkyl diphenylamine),T308(isooctyl acid thiophospholipid octadecylamine),and T306(trimethylphenol phosphate),separately,in order to screen for the optimal combination of spectral bands for each additive.The ACO algorithm was used to optimize the parameters of the XGBoost algorithm to improve the identification accuracy.During this process,the support vector machine(SVM)and hybrid bat algorithms(HBA)were included as a comparison,generating four models:ACO-XGBoost,ACO-SVM,HBA-XGboost,and HBA-SVM.The results showed that all four models could identify the three additives efficiently,with the ACO-XGBoost model achieving 100%recognition of all three additives.In addition,the generalizability of the ACO-XGBoost model was further demonstrated by predicting a lubricating oil containing the three additives prepared in our laboratory and a collected sample of commercial oil currently in use。 展开更多
关键词 lubricant oil additives fourier transform infrared spectroscopy type identification ACO-XGBoost combinatorial algorithm
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WSN Mobile Target Tracking Based on Improved Snake-Extended Kalman Filtering Algorithm 被引量:1
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作者 Duo Peng Kun Xie Mingshuo Liu 《Journal of Beijing Institute of Technology》 EI CAS 2024年第1期28-40,共13页
A wireless sensor network mobile target tracking algorithm(ISO-EKF)based on improved snake optimization algorithm(ISO)is proposed to address the difficulty of estimating initial values when using extended Kalman filte... A wireless sensor network mobile target tracking algorithm(ISO-EKF)based on improved snake optimization algorithm(ISO)is proposed to address the difficulty of estimating initial values when using extended Kalman filtering to solve the state of nonlinear mobile target tracking.First,the steps of extended Kalman filtering(EKF)are introduced.Second,the ISO is used to adjust the parameters of the EKF in real time to adapt to the current motion state of the mobile target.Finally,the effectiveness of the algorithm is demonstrated through filtering and tracking using the constant velocity circular motion model(CM).Under the specified conditions,the position and velocity mean square error curves are compared among the snake optimizer(SO)-EKF algorithm,EKF algorithm,and the proposed algorithm.The comparison shows that the proposed algorithm reduces the root mean square error of position by 52%and 41%compared to the SOEKF algorithm and EKF algorithm,respectively. 展开更多
关键词 wireless sensor network(WSN)target tracking snake optimization algorithm extended Kalman filter maneuvering target
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Ka-Band metalens antenna empowered by physics-assisted particle swarm optimization(PA-PSO)algorithm 被引量:1
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作者 Shibin Jiang Wenjun Deng +4 位作者 Zhanshan Wang Xinbin Cheng Din Ping Tsai Yuzhi Shi Weiming Zhu 《Opto-Electronic Science》 2024年第10期23-33,共11页
Design of multiple-feed lens antennas requires multivariate and multi-objective optimization processes,which can be accelerated by PSO algorithms.However,the PSO algorithm often fails to achieve optimal results with l... Design of multiple-feed lens antennas requires multivariate and multi-objective optimization processes,which can be accelerated by PSO algorithms.However,the PSO algorithm often fails to achieve optimal results with limited computation resources since spaces of candidate solutions are quite large for lens antenna designs.This paper presents a design paradigm for multiple-feed lens antennas based on a physics-assisted particle swarm optimization(PA-PSO)algorithm,which guides the swarm of particles based on laws of physics.As a proof of concept,a design of compact metalens antenna is proposed,which measures unprecedented performances,such as a field of view at±55°,a 21.7 dBi gain with a flatness within 4 dB,a 3-dB bandwidth>12°,and a compact design with a f-number of 0.2.The proposed PA-PSO algorithm reaches the optimal results 6 times faster than the ordinary PSO algorithm,which endows promising applications in the multivariate and multi-objective optimization processes,including but not limited to metalens antenna designs. 展开更多
关键词 multiple-feed lens antennas PA-PSO algorithm metalens metasurfaces Ka-band antenna
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一种面向COSPAS/SARSAT系统的改进载波同步算法及其FPGA实现
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作者 赵来定 聂良峰 张更新 《现代雷达》 CSCD 北大核心 2024年第12期73-82,共10页
为了实现全球卫星搜救系统中短突发信号的快速载波同步,文中提出了一种基于非数据辅助的改进载波同步算法。该算法首先对输入信号进行非线性处理来消除调制影响,再求取其自相关与共轭相关差值并得出频偏估计值,进行频偏补偿后再通过分... 为了实现全球卫星搜救系统中短突发信号的快速载波同步,文中提出了一种基于非数据辅助的改进载波同步算法。该算法首先对输入信号进行非线性处理来消除调制影响,再求取其自相关与共轭相关差值并得出频偏估计值,进行频偏补偿后再通过分段累加和相位跳变检测来完成相偏恢复。该算法在信号处理过程中进行部分相位调整措施,有效提高载波频偏估计精度和降低误码率。实验结果表明:该改进算法在采样频率f s为153.6 kHz时,频偏估计范围为±12 kHz;信噪比为10 dB时,误码率为1.36×10^(-5)。同时,文中给出了该改进载波同步算法的可编程门阵列实现结构,并进行了板级测试验证,测试结果表明其硬件资源消耗不足总系统资源的10%,能满足全球卫星搜救系统中搜救终端短突发信号的载波同步的各项技术指标。 展开更多
关键词 全球卫星搜救系统 改进载波同步算法 频偏估计 相偏估计 可编程门阵列实现
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Hybrid Prairie Dog and Beluga Whale Optimization Algorithm for Multi-Objective Load Balanced-Task Scheduling in Cloud Computing Environments
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作者 K Ramya Senthilselvi Ayothi 《China Communications》 SCIE CSCD 2024年第7期307-324,共18页
The cloud computing technology is utilized for achieving resource utilization of remotebased virtual computer to facilitate the consumers with rapid and accurate massive data services.It utilizes on-demand resource pr... The cloud computing technology is utilized for achieving resource utilization of remotebased virtual computer to facilitate the consumers with rapid and accurate massive data services.It utilizes on-demand resource provisioning,but the necessitated constraints of rapid turnaround time,minimal execution cost,high rate of resource utilization and limited makespan transforms the Load Balancing(LB)process-based Task Scheduling(TS)problem into an NP-hard optimization issue.In this paper,Hybrid Prairie Dog and Beluga Whale Optimization Algorithm(HPDBWOA)is propounded for precise mapping of tasks to virtual machines with the due objective of addressing the dynamic nature of cloud environment.This capability of HPDBWOA helps in decreasing the SLA violations and Makespan with optimal resource management.It is modelled as a scheduling strategy which utilizes the merits of PDOA and BWOA for attaining reactive decisions making with respect to the process of assigning the tasks to virtual resources by considering their priorities into account.It addresses the problem of pre-convergence with wellbalanced exploration and exploitation to attain necessitated Quality of Service(QoS)for minimizing the waiting time incurred during TS process.It further balanced exploration and exploitation rates for reducing the makespan during the task allocation with complete awareness of VM state.The results of the proposed HPDBWOA confirmed minimized energy utilization of 32.18% and reduced cost of 28.94% better than approaches used for investigation.The statistical investigation of the proposed HPDBWOA conducted using ANOVA confirmed its efficacy over the benchmarked systems in terms of throughput,system,and response time. 展开更多
关键词 Beluga Whale Optimization algorithm(BWOA) cloud computing Improved Hopcroft-Karp algorithm Infrastructure as a Service(IaaS) Prairie Dog Optimization algorithm(PDOA) Virtual Machine(VM)
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Hybrid Seagull and Whale Optimization Algorithm-Based Dynamic Clustering Protocol for Improving Network Longevity in Wireless Sensor Networks
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作者 P.Vinoth Kumar K.Venkatesh 《China Communications》 SCIE CSCD 2024年第10期113-131,共19页
Energy efficiency is the prime concern in Wireless Sensor Networks(WSNs) as maximized energy consumption without essentially limits the energy stability and network lifetime. Clustering is the significant approach ess... Energy efficiency is the prime concern in Wireless Sensor Networks(WSNs) as maximized energy consumption without essentially limits the energy stability and network lifetime. Clustering is the significant approach essential for minimizing unnecessary transmission energy consumption with sustained network lifetime. This clustering process is identified as the Non-deterministic Polynomial(NP)-hard optimization problems which has the maximized probability of being solved through metaheuristic algorithms.This adoption of hybrid metaheuristic algorithm concentrates on the identification of the optimal or nearoptimal solutions which aids in better energy stability during Cluster Head(CH) selection. In this paper,Hybrid Seagull and Whale Optimization Algorithmbased Dynamic Clustering Protocol(HSWOA-DCP)is proposed with the exploitation benefits of WOA and exploration merits of SEOA to optimal CH selection for maintaining energy stability with prolonged network lifetime. This HSWOA-DCP adopted the modified version of SEagull Optimization Algorithm(SEOA) to handle the problem of premature convergence and computational accuracy which is maximally possible during CH selection. The inclusion of SEOA into WOA improved the global searching capability during the selection of CH and prevents worst fitness nodes from being selected as CH, since the spiral attacking behavior of SEOA is similar to the bubble-net characteristics of WOA. This CH selection integrates the spiral attacking principles of SEOA and contraction surrounding mechanism of WOA for improving computation accuracy to prevent frequent election process. It also included the strategy of levy flight strategy into SEOA for potentially avoiding premature convergence to attain better trade-off between the rate of exploration and exploitation in a more effective manner. The simulation results of the proposed HSWOADCP confirmed better network survivability rate, network residual energy and network overall throughput on par with the competitive CH selection schemes under different number of data transmission rounds.The statistical analysis of the proposed HSWOA-DCP scheme also confirmed its energy stability with respect to ANOVA test. 展开更多
关键词 CLUSTERING energy stability network lifetime seagull optimization algorithm(SEOA) whale optimization algorithm(WOA) wireless sensor networks(WSNs)
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