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Seismic Data Reconstruction and Noise Suppression Based on an Improved Weighted Fast Projection onto Convex Sets Algorithm 认领 引用
1
作者 Cheng Gao-peng Zhang Hua +3 位作者 Li Hong-xing Song Yu Yue Ming Zhang Kai-dong 《Applied Geophysics》 SCIE CSCD 2026年第1期336-351,433,434,共16页
In eld seismic data acquisition,seismic traces are often aected by substantial data gaps and strong noise interference due to environmental and instrumental factors,thus degrading the resolution and signalto-noise rat... In eld seismic data acquisition,seismic traces are often aected by substantial data gaps and strong noise interference due to environmental and instrumental factors,thus degrading the resolution and signalto-noise ratio(SNR)of the seismic profiles.Effective seismic data reconstruction and noise suppression techniques are therefore essential to recover missing signals and improve data quality.In this study,a fast projection onto convex sets(FPOCS)algorithm is proposed by incorporating an inertial parameter that involves a linear combination of the two preceding iterations based on the traditional projection onto convex sets(POCS)algorithm.Then,a weighting factor is introduced to achieve simultaneous data reconstruction and noise suppression using the weighted fast projection onto convex sets(WFPOCS)algorithm.To further suppress residual random noise in the updated solution,an optimization strategy is adopted by swapping the order of the iterative hard thresholding operator and the projection operator.The nal algorithm,termed the improved weighted fast projection onto convex sets(IWFPOCS),achieves high-efciency reconstruction and effective noise suppression.Compared with WFPOCS,the proposed method maintains fast reconstruction speed while demonstrating superior denoising performance on irregularly missing and noisy datasets.Field data experiments conrm that the proposed method signicantly improves the SNR and resolution of seismic data,oering strong practical potential for subsequent processing and interpretation. 展开更多
关键词 Seismic data reconstruction Fast projection onto convex set algorithm Curvelet transform Weighted fast projection onto convex set algorithm Noise suppression
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A fast algorithm for solving the scattering problem from an open rectangular cavity 认领 引用
2
作者 HAN Shangqi LI Yuan 《黑龙江大学自然科学学报》 CAS 2026年第1期31-41,共11页
This paper presents a fast algorithm for solving the scattering problem from an open rectangular cavity embedded in the ground plane.The computational region is chosen as the union of two rectangular regions:one is a ... This paper presents a fast algorithm for solving the scattering problem from an open rectangular cavity embedded in the ground plane.The computational region is chosen as the union of two rectangular regions:one is a region above the ground,the other one is a region containing the cavity.The finite difference scheme is constructed in each region.An intermediate layer of the mesh is shared by both regions,which is the key of the algorithm.A cyclic reduction method is employed to solve the difference equation in the region above the ground.Then the numerical solution on the cavity aperture can be obtained.The numerical experiments are provided to verify the feasibility of the proposed algorithm. 展开更多
关键词 scattering problem cavity Helmholtz equation fast algorithm difference equation cyclic reduction method
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Self-adaptive PID controller of microwave drying rotary device tuning on-line by genetic algorithms 认领 引用 被引量：8
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作者 杨彪 梁贵安 +5 位作者 彭金辉 郭胜惠 李玮 张世敏 李英伟 白松 《Journal of Central South University》 SCIE EI CAS 2013年第10期2685-2692,共8页
The control design, based on self-adaptive PID with genetic algorithms(GA) tuning on-line was investigated, for the temperature control of industrial microwave drying rotary device with the multi-layer(IMDRDWM) and wi... The control design, based on self-adaptive PID with genetic algorithms(GA) tuning on-line was investigated, for the temperature control of industrial microwave drying rotary device with the multi-layer(IMDRDWM) and with multivariable nonlinear interaction of microwave and materials. The conventional PID control strategy incorporated with optimization GA was put forward to maintain the optimum drying temperature in order to keep the moisture content below 1%, whose adaptation ability included the cost function of optimization GA according to the output change. Simulations on five different industrial process models and practical temperature process control system for selenium-enriched slag drying intensively by using IMDRDWM were carried out systematically, indicating the reliability and effectiveness of control design. The parameters of proposed control design are all on-line implemented without iterative predictive calculations, and the closed-loop system stability is guaranteed, which makes the developed scheme simpler in its synthesis and application, providing the practical guidelines for the control implementation and the parameter design. 展开更多
关键词 industrial microwave drying rotary device self-adaptive PID controller genetic algorithm on-line tuning selenium-enriched slag
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Acid-pickling plates and strips speed control system by microwave heating based on self-adaptive fuzzy PID algorithm 认领 引用 被引量：9
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作者 杨彪 彭金辉 +3 位作者 郭胜惠 张世敏 李玮 何涛 《Journal of Central South University》 SCIE EI CAS 2012年第8期2179-2186,共8页
Double self-adaptive fuzzy PID algorithm-based control strategy was proposed to construct quasi-cascade control system to control the speed of the acid-pickling process of titanium plates and strips. It is very useful... Double self-adaptive fuzzy PID algorithm-based control strategy was proposed to construct quasi-cascade control system to control the speed of the acid-pickling process of titanium plates and strips. It is very useful in overcoming non-linear dynamic behavior, uncertain and time-varying parameters, un-modeled dynamics, and couples between the automatic turbulence control (ATC) and the automatic acid temperature control (AATC) with varying parameters during the operation process. The quasi-cascade control system of inner and outer loop self-adaptive fuzzy PID controller was built, which could effectively control the pickling speed of plates and strips. The simulated results and real application indicate that the plates and strips acid pickling speed control system has good performances of adaptively tracking the parameter variations and anti-disturbances, which ensures the match of acid pickling temperature and turbulence of flowing with acid pickling speed, improving the surface quality of plates and strips acid pickling, and energy efficiency. 展开更多
关键词 self-adaptive fuzzy PID algorithm microwave heating acid pickling plates and strips mixed-acid media
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Modified Self-adaptive Immune Genetic Algorithm for Optimization of Combustion Side Reaction of p-Xylene Oxidation 认领 引用 被引量：3
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作者 陶莉莉 孔祥东 +1 位作者 钟伟民 钱锋 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2012年第6期1047-1052,共6页
In recent years, immune genetic algorithm (IGA) is gaining popularity for finding the optimal solution for non-linear optimization problems in many engineering applications. However, IGA with deterministic mutation fa... In recent years, immune genetic algorithm (IGA) is gaining popularity for finding the optimal solution for non-linear optimization problems in many engineering applications. However, IGA with deterministic mutation factor suffers from the problem of premature convergence. In this study, a modified self-adaptive immune genetic algorithm (MSIGA) with two memory bases, in which immune concepts are applied to determine the mutation parameters, is proposed to improve the searching ability of the algorithm and maintain population diversity. Performance comparisons with other well-known population-based iterative algorithms show that the proposed method converges quickly to the global optimum and overcomes premature problem. This algorithm is applied to optimize a feed forward neural network to measure the content of products in the combustion side reaction of p-xylene oxidation, and satisfactory results are obtained. 展开更多
关键词 self-adaptive immune genetic algorithm artificial neural network measurement p-xylene oxidation process
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Enhanced self-adaptive evolutionary algorithm for numerical optimization 认领 引用 被引量：2
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作者 Yu Xue YiZhuang +2 位作者 Tianquan Ni Jian Ouyang ZhouWang 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2012年第6期921-928,共8页
There are many population-based stochastic search algorithms for solving optimization problems. However, the universality and robustness of these algorithms are still unsatisfactory. This paper proposes an enhanced se... There are many population-based stochastic search algorithms for solving optimization problems. However, the universality and robustness of these algorithms are still unsatisfactory. This paper proposes an enhanced self-adaptiveevolutionary algorithm （ESEA） to overcome the demerits above. In the ESEA, four evolutionary operators are designed to enhance the evolutionary structure. Besides, the ESEA employs four effective search strategies under the framework of the self-adaptive learning. Four groups of the experiments are done to find out the most suitable parameter values for the ESEA. In order to verify the performance of the proposed algorithm, 26 state-of-the-art test functions are solved by the ESEA and its competitors. The experimental results demonstrate that the universality and robustness of the ESEA out-perform its competitors. 展开更多
关键词 self-adaptive numerical optimization evolutionary al-gorithm stochastic search algorithm.
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Generalized Self-Adaptive Genetic Algorithms 认领 引用 被引量：2
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作者 Bin Wu Xuyan Tu +1 位作者 Jian Wu Information Engineering School, University of Science and Technology Beijing, Beijing 100083, China Department of Information and Control Engineering, Southwest Institute of Technology, Mianyang 621002, China 《International Journal of Minerals,Metallurgy and Materials》 SCIE EI CAS 2000年第1期72-75,共4页
In order to solve the problem between searching performance and convergence of genetic algorithms, a fast genetic algorithm generalized self-adaptive genetic algorithm (GSAGA) is presented. (1) Evenly distributed init... In order to solve the problem between searching performance and convergence of genetic algorithms, a fast genetic algorithm generalized self-adaptive genetic algorithm (GSAGA) is presented. (1) Evenly distributed initial population is generated. (2) Superior individuals are not broken because of crossover and mutation operation for they are sent to subgeneration directly. (3) High quality im- migrants are introduced according to the condition of the population schema. (4) Crossover and mutation are operated on self-adaptation. Therefore, GSAGA solves the coordination problem between convergence and searching performance. In GSAGA, the searching per- formance and global convergence are greatly improved compared with many existing genetic algorithms. Through simulation, the val- idity of this modified genetic algorithm is proved. 展开更多
关键词 generalized self-adaptive genetic algorithm initial population immigration fitness function
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Dynamic self-adaptive ANP algorithm and its application to electric field simulation of aluminum reduction cell 认领 引用 被引量：2
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作者 王雅琳 陈冬冬 +2 位作者 陈晓方 蔡国民 阳春华 《Journal of Central South University》 SCIE EI CAS CSCD 2015年第12期4731-4739,共9页
Region partition(RP) is the key technique to the finite element parallel computing(FEPC),and its performance has a decisive influence on the entire process of analysis and computation.The performance evaluation index ... Region partition(RP) is the key technique to the finite element parallel computing(FEPC),and its performance has a decisive influence on the entire process of analysis and computation.The performance evaluation index of RP method for the three-dimensional finite element model(FEM) has been given.By taking the electric field of aluminum reduction cell(ARC) as the research object,the performance of two classical RP methods,which are Al-NASRA and NGUYEN partition(ANP) algorithm and the multi-level partition(MLP) method,has been analyzed and compared.The comparison results indicate a sound performance of ANP algorithm,but to large-scale models,the computing time of ANP algorithm increases notably.This is because the ANP algorithm determines only one node based on the minimum weight and just adds the elements connected to the node into the sub-region during each iteration.To obtain the satisfied speed and the precision,an improved dynamic self-adaptive ANP(DSA-ANP) algorithm has been proposed.With consideration of model scale,complexity and sub-RP stage,the improved algorithm adaptively determines the number of nodes and selects those nodes with small enough weight,and then dynamically adds these connected elements.The proposed algorithm has been applied to the finite element analysis(FEA) of the electric field simulation of ARC.Compared with the traditional ANP algorithm,the computational efficiency of the proposed algorithm has been shortened approximately from 260 s to 13 s.This proves the superiority of the improved algorithm on computing time performance. 展开更多
关键词 finite element parallel computing(FEPC) region partition(RP) dynamic self-adaptive ANP(DSA-ANP) algorithm electric field simulation aluminum reduction cell(ARC)
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Differential Evolution Algorithm Based Self-adaptive Control Strategy for Fed-batch Cultivation of Yeast 认领 引用
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作者 Aiyun Hu Sunli Cong +2 位作者 Jian Ding Yao Cheng Enock Mpofu 《Computer Systems Science & Engineering》 SCIE EI 2021年第7期65-77,共13页
In the fed-batch cultivation of Saccharomyces cerevisiae,excessive glucose addition leads to increased ethanol accumulation,which will reduce the efficiency of glucose utilization and inhibit product synthesis.Insuffi... In the fed-batch cultivation of Saccharomyces cerevisiae,excessive glucose addition leads to increased ethanol accumulation,which will reduce the efficiency of glucose utilization and inhibit product synthesis.Insufficient glucose addition limits cell growth.To properly regulate glucose feed,a different evolution algorithm based on self-adaptive control strategy was proposed,consisting of three modules(PID,system identification and parameter optimization).Performance of the proposed and conventional PID controllers was validated and compared in simulated and experimental cultivations.In the simulation,cultivation with the self-adaptive control strategy had a more stable glucose feed rate and concentration,more stable ethanol concentration around the set-point(1.0 g·L-1),and final biomass concentration of 34.5 g-DCW·L-1,29.2%higher than that with a conventional PID control strategy.In the experiment,the cultivation with the self-adaptive control strategy also had more stable glucose and ethanol concentrations,as well as a final biomass concentration that was 37.4%higher than that using the conventional strategy. 展开更多
关键词 Saccharomyces cerevisiae Ethanol accumulation differential evolution algorithm self-adaptive control
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Unfolding neutron spectra from water-pumping-injection multilayered concentric sphere neutron spectrometer using self-adaptive differential evolution algorithm 认领 引用 被引量：6
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作者 Rui Li Jian-Bo Yang +2 位作者 Xian-Guo Tuo Jie Xu Rui Shi 《Nuclear Science and Techniques》 SCIE EI CAS CSCD 2021年第3期41-51,共11页
A self-adaptive differential evolution neutron spectrum unfolding algorithm(SDENUA)is established in this study to unfold the neutron spectra obtained from a water-pumping-injection multilayered concentric sphere neut... A self-adaptive differential evolution neutron spectrum unfolding algorithm(SDENUA)is established in this study to unfold the neutron spectra obtained from a water-pumping-injection multilayered concentric sphere neutron spectrometer(WMNS).Specifically,the neutron fluence bounds are estimated to accelerate the algorithm convergence,and the minimum error between the optimal solution and input neutron counts with relative uncertainties is limited to 10-6to avoid unnecessary calculations.Furthermore,the crossover probability and scaling factor are self-adaptively controlled.FLUKA Monte Carlo is used to simulate the readings of the WMNS under(1)a spectrum of Cf-252 and(2)its spectrum after being moderated,(3)a spectrum used for boron neutron capture therapy,and(4)a reactor spectrum.Subsequently,the measured neutron counts are unfolded using the SDENUA.The uncertainties of the measured neutron count and the response matrix are considered in the SDENUA,which does not require complex parameter tuning or an a priori default spectrum.The results indicate that the solutions of the SDENUA agree better with the IAEA spectra than those of MAXED and GRAVEL in UMG 3.1,and the errors of the final results calculated using the SDENUA are less than 12%.The established SDENUA can be used to unfold spectra from the WMNS. 展开更多
关键词 Water-pumping-injection multilayered spectrometer Neutron spectrum unfolding Differential evolution algorithm Self-adaptive control
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An improved self-adaptive membrane computing optimization algorithm and its applications in residue hydrogenating model parameter estimation 认领 引用 被引量：1
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作者 芦会彬 薄翠梅 杨世品 《Journal of Central South University》 SCIE EI CAS CSCD 2015年第10期3909-3915,共7页
In order to solve the non-linear and high-dimensional optimization problems more effectively, an improved self-adaptive membrane computing(ISMC) optimization algorithm was proposed. The proposed ISMC algorithm applied... In order to solve the non-linear and high-dimensional optimization problems more effectively, an improved self-adaptive membrane computing(ISMC) optimization algorithm was proposed. The proposed ISMC algorithm applied improved self-adaptive crossover and mutation formulae that can provide appropriate crossover operator and mutation operator based on different functions of the objects and the number of iterations. The performance of ISMC was tested by the benchmark functions. The simulation results for residue hydrogenating kinetics model parameter estimation show that the proposed method is superior to the traditional intelligent algorithms in terms of convergence accuracy and stability in solving the complex parameter optimization problems. 展开更多
关键词 optimization algorithm membrane computing benchmark function improved self-adaptive operator
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Fast beam migration capable of dealing with intersecting events 认领 引用
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作者 Zhi-Miao Chang Fu-Xing Han +4 位作者 Zheng-Hui Gao Zhang-Qing Sun Shou-Dong Huo Gang Li Ming Zhang 《Petroleum Science》 SCIE EI CAS CSCD 2026年第1期190-204,共15页
Fast beam migration(FBM),characterized by its super-high efficiency in velocity model building,consists of three main steps:beam forming,beam propagation,and image forming.The super-high efficiency is achieved by beam... Fast beam migration(FBM),characterized by its super-high efficiency in velocity model building,consists of three main steps:beam forming,beam propagation,and image forming.The super-high efficiency is achieved by beam forming,as it needs only to be performed once for one dataset and is independent of velocity,and the other two steps take relatively little time.However,compared to the beam-propagation and image-forming steps,the beam-forming step is still quite time-consuming owing to the high-dimensional computing problem of estimating the source and receiver slope orientation of a beam.Furthermore,previous methods for estimating the source and receiver slope orientation of a beam struggled to deal with intersecting events,leading to poor imaging results for complex subsurface structures,such as unconformities or faults,where events often intersect.We propose the use of a three-step multimodal optimization method based on the neighborhood crowding differential evolution(NCDE)algorithm to estimate the source and receiver slope orientation of a beam during the beam-forming step,which can quickly and accurately obtain slope orientations when events intersect.We first test the three-step multimodal optimization algorithm on a 3D super-gather and provide the parameter criteria.We then apply the FBM based on the three-step multimodal optimization algorithm to the Marmousi 2 and 3D SEG/EAGE salt models.Both results demonstrate that the proposed method can image intersecting events well and that the imaging quality of complex zones is improved.We also apply the proposed method to a 2D offshore seismic dataset containing abundant intersecting events,which validates the practicality of the proposed method. 展开更多
关键词 Fast beam migration(FBM) Intersecting events Multimodal optimization method Neighborhood crowding differential evolution(NCDE)algorithm High-dimensional computing problem
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结合车辆追踪技术与FastDTW算法的桥梁动态称重方法 认领 引用
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作者 靳阳 杨干 +4 位作者 陈鹏涛 王涛 陈适之 王红霞 韩万水 《中国公路学报》 EI CAS CSCD 北大核心 2026年第6期267-281,共15页
传统桥梁动态称重算法往往假设车辆匀速直线行驶,且默认上下桥时刻已知。然而,在实际工程中,车辆行驶特征复杂,上下桥时刻也难以从监测数据精确获取。为解决这些难题,提出一种融合计算机视觉技术与快速动态时间规整(FastDTW)算法的桥梁... 传统桥梁动态称重算法往往假设车辆匀速直线行驶,且默认上下桥时刻已知。然而,在实际工程中,车辆行驶特征复杂,上下桥时刻也难以从监测数据精确获取。为解决这些难题,提出一种融合计算机视觉技术与快速动态时间规整(FastDTW)算法的桥梁动态称重方法。该方法能充分考虑车辆真实行驶特性,即便上下桥时间存在偏差,仍可实现精准称重。在具体操作流程上,先利用计算机视觉技术识别、追踪车辆,获取其时空信息;接着结合车辆重量统计数据,初始化车辆荷载,为后续迭代求解真实车辆荷载提供原始数据。然后,借助FastDTW算法关联桥梁响应的计算与实测时程曲线,通过不断迭代调整轴距、轴重信息,使两者逐步逼近,进而得到准确的车辆轴距和轴重。经模拟计算与模型试验验证,该方法在考虑车辆加减速、变道等行驶特征时,轴距、轴重识别平均相对误差仅为2.83%和2.67%,最大相对误差分别为5.60%和5.84%,总重最大相对误差为4.28%。此外,在实桥试验验证中,最大轴距、最大轴重识别相对误差分别为10.03%和6.16%,最大总重识别相对误差为5.72%。这充分展现出该算法的准确性与适用性,应用前景十分广阔。 展开更多
关键词 桥梁工程 桥梁动态称重 计算机视觉技术 动态时间规整算法 车辆行驶特征
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Self-Adaptive Algorithms for the Split Common Fixed Point Problem of the Demimetric Mappings 认领 引用 被引量：1
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作者 Xinhong Chen Yanlai Song +1 位作者 Jianying He Liping Gong 《Journal of Applied Mathematics and Physics》 2019年第10期2187-2199,共13页
The split common fixed point problem is an inverse problem that consists in finding an element in a fixed point set such that its image under a bounded linear operator belongs to another fixed-point set. In this paper... The split common fixed point problem is an inverse problem that consists in finding an element in a fixed point set such that its image under a bounded linear operator belongs to another fixed-point set. In this paper, we present new iterative algorithms for solving the split common fixed point problem of demimetric mappings in Hilbert spaces. Moreover, our algorithm does not need any prior information of the operator norm. Weak and strong convergence theorems are given under some mild assumptions. The results in this paper are the extension and improvement of the recent results in the literature. 展开更多
关键词 Hilbert Space Demimetric Mapping Split Common Fixed Point Problem Self-Adaptive Algorithm
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Joint Access Node Selection and Fast Routing Optimization for LEO Satellite Networks 认领 引用
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作者 Zhang Yifan Dong Tao +2 位作者 Liu Zhihui Di Hang Zhou Jianming 《China Communications》 SCIE EI CSCD 2026年第6期146-164,共19页
The low Earth orbit(LEO)satellite networks play an important role in the future communication networks.However,under the end-to-end(E2E)transmission background,inter-satellite routing has been widely studied,but the i... The low Earth orbit(LEO)satellite networks play an important role in the future communication networks.However,under the end-to-end(E2E)transmission background,inter-satellite routing has been widely studied,but the influence of ground-satellite links(GSL)on routing has received less attention.In this paper,a fast E2E satellite routing algorithm based on access node selection is proposed.Firstly,the delay of four path modes generated by users accessing the network from different satellites is analyzed,and the influence of delay on E2E routing performance is presented.Then,jointly considering routing delay and node load,an access node selection strategy is proposed by using the shortest E2E delay to determine the access source and destination node within satellites.Finally,an optimization domain is divided from the network topology by using the shortest delay path based on hops constraints.And a routing optimization algorithm based on Q-learning has been proposed in the optimization domain,realizing high computational speed and stable results.The simulation results show that the access node selection strategy can decrease E2E delay by up to 10 ms and enhance the performance of node load balancing.And the routing optimization algorithm can reduce the average computation time. 展开更多
关键词 access selection fast routing LEO satellite networks load balancing routing algorithm
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Particle Swarm Optimization Algorithm Based on Chaotic Sequences and Dynamic Self-Adaptive Strategy 认领 引用
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作者 Mengshan Li Liang Liu +4 位作者 Genqin Sun Keming Su Huaijin Zhang Bingsheng Chen Yan Wu 《Journal of Computer and Communications》 2017年第12期13-23,共11页
To deal with the problems of premature convergence and tending to jump into the local optimum in the traditional particle swarm optimization, a novel improved particle swarm optimization algorithm was proposed. The se... To deal with the problems of premature convergence and tending to jump into the local optimum in the traditional particle swarm optimization, a novel improved particle swarm optimization algorithm was proposed. The self-adaptive inertia weight factor was used to accelerate the converging speed, and chaotic sequences were used to tune the acceleration coefficients for the balance between exploration and exploitation. The performance of the proposed algorithm was tested on four classical multi-objective optimization functions by comparing with the non-dominated sorting genetic algorithm and multi-objective particle swarm optimization algorithm. The results verified the effectiveness of the algorithm, which improved the premature convergence problem with faster convergence rate and strong ability to jump out of local optimum. 展开更多
关键词 Particle Swarm Algorithm Chaotic Sequences Self-Adaptive Strategy Multi-Objective Optimization
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Improvement and performance of parallel multilevel fast multipole algorithm 认领 引用 被引量：16
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作者 Zhanhe Liu Peilin Huang +1 位作者 Zhe Wu Xu Gao 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2011年第1期164-169,共6页
The method of establishing data structures plays an important role in the efficiency of parallel multilevel fast multipole algorithm（PMLFMA）.Considering the main complements of multilevel fast multipole algorithm（M... The method of establishing data structures plays an important role in the efficiency of parallel multilevel fast multipole algorithm（PMLFMA）.Considering the main complements of multilevel fast multipole algorithm（MLFMA） memory,a new parallelization strategy and a modified data octree construction scheme are proposed to further reduce communication in order to improve parallel efficiency.For far interaction,a new scheme called dynamic memory allocation is developed.To analyze the workload balancing performance of a parallel implementation,the original concept of workload balancing factor is introduced and verified by numerical examples.Numerical results show that the above measures improve the parallel efficiency and are suitable for the analysis of electrical large-scale scattering objects. 展开更多
关键词 multilevel fast multipole algorithm（MLFMA） electromagnetic scattering parallelization radar cross section（RCS）.
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Fast period estimation of X-ray pulsar signals using an improved fast folding algorithm 认领 引用 被引量：2
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作者 Minzhang SONG Yidi WANG +4 位作者 Wei ZHENG Liansheng LI Yusong WANG Xiaowei HU Yulong WU 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2023年第10期309-316,共8页
An accurate period is important to recover the pulse profile from a recorded photon event series of an X-ray pulsar and to estimate the pulse time of arrival,which is the measurement of X-ray pulsar navigation.Epoch f... An accurate period is important to recover the pulse profile from a recorded photon event series of an X-ray pulsar and to estimate the pulse time of arrival,which is the measurement of X-ray pulsar navigation.Epoch folding is a classical period estimation method in the time domain;however,its computational complexity grows as the number of trail periods increases.In order to reduce the computational complexity,this paper improves the fast folding algorithm through segment correlation and amplitude accumulation,which is based on the post-order traversal of a binary tree.Compared with epoch folding,the improved fast folding algorithm can achieve a similar accuracy at the cost of a lower computational burden.Compared with the original fast folding algorithm,the improved algorithm can be applied to detectors with a much smaller effective area.The performance of the method is investigated by simulation data and observation data from the Neutron star Interior Composition Explorer(NICER). 展开更多
关键词 Epoch folding Fast folding algorithm Pulsar spin period Phase estimation X-ray pulsar
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Fast algorithm for constructing neighbor-joining phylogenetic trees 认领 引用 被引量：4
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作者 陈宁涛 王能超 施保昌 《Journal of Southeast University(English Edition)》 EI CAS 2006年第2期176-179,共4页
To improve the performance of Saitou and Nei＇s algorithm （SN） and Studier and Keppler＇s improved algorithm （SK） for constructing neighbor-joining phylogenetic trees and reduce the time complexity of the computat... To improve the performance of Saitou and Nei＇s algorithm （SN） and Studier and Keppler＇s improved algorithm （SK） for constructing neighbor-joining phylogenetic trees and reduce the time complexity of the computation, a fast algorithm is proposed. The proposed algorithm includes three techniques. First, a linear array A[N] is introduced to store the sum of every row of the distance matrix （the same as SK）, which can eliminate many repeated computations. Secondly, the value of A [i] is computed only once at the beginning of the algorithm, and is updated by three elements in the iteration. Thirdly, a very compact formula for the sum of all the branch lengths of operational taxonomic units （OTUs） i and j is designed, and the correctness of the formula is proved. The experimental results show that the proposed algorithm is from tens to hundreds times faster than SN and roughly two times faster than SK when N increases, constructing a tree with 2 000 OTUs in 3 min on a current desktop computer. To earn the time with the cost of the space and reduce the computations in the innermost loop are the basic solutions for algorithms with many loops. 展开更多
关键词 phylogenetic tree neighbor-joining method fast algorithm progressive multiple alignment
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An adaptive reanalysis method for genetic algorithm with application to fast truss optimization 认领 引用 被引量：3
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作者 Tao Xu Wenjie Zuo +2 位作者 Tianshuang Xu Guangcai Song Ruichuan Li 《Acta Mechanica Sinica》 SCIE EI CAS 2010年第2期225-234,共10页
Although the genetic algorithm （GA） for structural optimization is very robust, it is very computationally intensive and hence slower than optimality criteria and mathematical programming methods. To speed up the de... Although the genetic algorithm （GA） for structural optimization is very robust, it is very computationally intensive and hence slower than optimality criteria and mathematical programming methods. To speed up the design process, the authors present an adaptive reanalysis method for GA and its applications in the optimal design of trusses. This reanalysis technique is primarily derived from the Kirsch＇s combined approximations method. An iteration scheme is adopted to adaptively determine the number of basis vectors at every generation. In order to illustrate this method, three classical examples of optimal truss design are used to validate the proposed reanalysis-based design procedure. The presented numerical results demonstrate that the adaptive reanalysis technique affects very slightly the accuracy of the optimal solutions and does accelerate the design process, especially for large-scale structures. 展开更多
关键词 Truss structure Adaptive reanalysis ·Genetic algorithm ·Fast optimization
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