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
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
Conventional empirical equations for estimating undrained shear strength(su)from piezocone penetration test(CPTu)data,without incorporating soil physical properties,often lack the accuracy and robustness required f...Conventional empirical equations for estimating undrained shear strength(su)from piezocone penetration test(CPTu)data,without incorporating soil physical properties,often lack the accuracy and robustness required for geotechnical site investigations.This study introduces a hybrid virus colony search(VCS)algorithm that integrates the standard VCS algorithm with a mutation-based search mechanism to develop high-performance XGBoost learning models to address this limitation.A dataset of 372 seismic CPTu and corresponding soil physical properties data from 26 geotechnical projects in JiangsuProvince,China,was collected for model development.Comparative evaluations demonstrate that the proposed hybrid VCS-XGBoost model exhibits superior performance compared to standard meta-heuristic algorithm-based XGBoost models.The results highlight that the consideration of soil physical properties significantly improves the predictive accuracy of su,emphasizing the importance of considering additional soil information beyond CPTu data for accurate suestimation.展开更多
Wafer probe testing is essential for evaluating the reliability of microelectronic devices.As device dimensions continue to shrink,the mechanical stress at the probe tip increases the risk of failure occurring in the ...Wafer probe testing is essential for evaluating the reliability of microelectronic devices.As device dimensions continue to shrink,the mechanical stress at the probe tip increases the risk of failure occurring in the brittle dielectric layer.Existing studies usually simplify the plastic behavior of bond pads in finite element(FE)models,making it difficult to accurately predict the stress in the dielectric layer.In this study,the FE model for wafer probe testing was improved by implanting the true plastic properties of Al-(4 wt.%)Cu bond pads obtained from nanoindentation inverse identification.Specifically,a MATLAB and ABAQUS co-simulation method is employed to inversely obtain the plastic properties of Al-(4 wt.%)Cu bond pads from the nanoindentation load-displacement curve.By comparing different gradient-based optimization algorithms,the Levenberg-Marquardt(LM)algorithm was found to be the most suitable for balancing computational efficiency and accuracy in inverse identification.Moreover,a hybrid optimization strategy combining Gauss-Newton and LM algorithms is proposed to mitigate sensitivity to initial values.The results show that the improved model of wafer probe testing achieves high accuracy in stress prediction.This study provides a high-fidelity approach for mechanical reliability assessment of wafer probe testing.展开更多
Traditional heuristic algorithms often fall into local optima and converge slowly when test case prioritization is addressed in regression testing,making them inadequate for complex real-world scenarios.The Aquila opt...Traditional heuristic algorithms often fall into local optima and converge slowly when test case prioritization is addressed in regression testing,making them inadequate for complex real-world scenarios.The Aquila optimizer,a novel metaheuristic algorithm,demonstrates strong global exploration capability but still faces limitations,including insufficient exploitation capability and slow convergence.To overcome these challenges,a multi-strategy improved chaotic Cauchy inverse cumulative distribution Aquila optimizer for test case prioritization is proposed.First,a logistic–sine–cosine composite chaotic mapping is introduced during the initialization phase of the Aquila optimizer to increase population diversity.Second,the mutated random walk strategy is used to improve global exploration,further enhancing the global search ability of the Aquila optimizer.Moreover,during the narrowed exploration and narrowed exploitation phases,the Cauchy inverse cumulative distribution flight replaces the Lévy flight strategy to reallocate individual positions,strengthening individuals’optimization capability and preventing the algorithm from becoming trapped in local optima.Finally,in the later iteration stage,the specular reflection learning strategy is used to perturb the optimal individual positions and improve the Aquila optimizer’s convergence accuracy and comprehensive optimization performance.Five Java projects were selected from the Defects4J benchmark datasets to conduct comparative experiments with the Aquila optimizer and seven other metaheuristic algorithms.The results demonstrate the effectiveness and superiority of the improved algorithm in test case prioritization.It achieves average improvements of approximately 4.96%in the average percentage of fault detection,3.82%in the average percentage of block coverage,and 5.64%in the average percentage of decision coverage,enabling faster coverage of code blocks and branches.The results provide an efficient priority sorting solution for complex regression testing scenarios.展开更多
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
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
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
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
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
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
Recently,a two-dimensional(2-D)Tsallis entropy thresholding method has been proposed as a new method for image segmentation.But the computation complexity of 2-D Tsallis entropy is very large and becomes an obstacle t...Recently,a two-dimensional(2-D)Tsallis entropy thresholding method has been proposed as a new method for image segmentation.But the computation complexity of 2-D Tsallis entropy is very large and becomes an obstacle to real time image processing systems.A fast recursive algorithm for 2-D Tsallis entropy thresholding is proposed.The key variables involved in calculating 2-D Tsallis entropy are written in recursive form.Thus,many repeating calculations are avoided and the computation complexity reduces to O(L2)from O(L4).The effectiveness of the proposed algorithm is illustrated by experimental results.展开更多
This paper is dedicated to applying the Fourier amplitude sensitivity test(FAST)method to the problem of mixed extension and inflation of a circular cylindrical tube in the presence of residual stresses.The metafuncti...This paper is dedicated to applying the Fourier amplitude sensitivity test(FAST)method to the problem of mixed extension and inflation of a circular cylindrical tube in the presence of residual stresses.The metafunctions and the Ishigami function are considered in the sensitivity analysis(SA).The effects of the input variables on the output variables are investigated,and the most important parameters of the system under the applied pressure and axial force such as the axial stretch and the azimuthal stretch are determined.展开更多
A full-wave analysis of the electromagnetic problem of a three-dimensional(3-D)antenna radiating through a 3-D dielectric radome is preserued.The problem is formulated using the Poggio-Miller-Chang-Harrington-Wu(PMCHW...A full-wave analysis of the electromagnetic problem of a three-dimensional(3-D)antenna radiating through a 3-D dielectric radome is preserued.The problem is formulated using the Poggio-Miller-Chang-Harrington-Wu(PMCHW)approach for homogeneous dielectric objects and the electric field integral equation for conducting objects.The integral equations are discretized by the method of moment(MoM),in which the conducting and dielectric surface/interfaces are represented by curvilinear triangular patches and the unknown equivalent electric and magnetic currents are expanded using curvilinear RWG basis functions.The resultant matrix equation is then solved by the multilevel fast multipole algorithm(MLFMA)and fast far-field approximation(FAFFA)is used to further accelerate the computation.The radiation patterns of dipole arrays in the presence of radomes are presented.The numerical results demonstrate the accuracy and versatility of this method.展开更多
A new efficient protocol-proving algorithm was proposed for verifying security protocols. This algorithm is based on the improved authentication tests model, which enhances the original model by formalizing the messag...A new efficient protocol-proving algorithm was proposed for verifying security protocols. This algorithm is based on the improved authentication tests model, which enhances the original model by formalizing the message reply attack. With exact causal dependency relations between messages in this model, the protocol-proving algorithm can avoid the state explosion caused by asynchronous. In order to get the straight proof of security protocols, three authentication theorems are exploited for evaluating the agreement and distinction properties. When the algorithm terminates, it outputs either the proof results or the potential flaws of the security protocol. The experiment shows that the protocol-proving algorithm can detect the type flaw attack on Neuman-Stubblebine protocol, and prove the correctness of NSL protocol by exploring only 10 states.展开更多
A general and efficient parallel approach is proposed for the first time to parallelize the hybrid finiteelement-boundary-integral-multi-level fast multipole algorithm(FE-BI-MLFMA).Among many algorithms of FE-BI-MLFMA...A general and efficient parallel approach is proposed for the first time to parallelize the hybrid finiteelement-boundary-integral-multi-level fast multipole algorithm(FE-BI-MLFMA).Among many algorithms of FE-BI-MLFMA,the decomposition algorithm(DA)is chosen as a basis for the parallelization of FE-BI-MLFMA because of its distinct numerical characteristics suitable for parallelization.On the basis of the DA,the parallelization of FE-BI-MLFMA is carried out by employing the parallelized multi-frontal method for the matrix from the finiteelement method and the parallelized MLFMA for the matrix from the boundary integral method respectively.The programming and numerical experiments of the proposed parallel approach are carried out in the high perfor-mance computing platform CEMS-Liuhui.Numerical experiments demonstrate that FE-BI-MLFMA is efficiently parallelized and its computational capacity is greatly improved without losing accuracy,efficiency,and generality.展开更多
The computation burden in the model-based predictive control algorithm is heavy when solving QR optimization with a limited sampling step, especially for a complicated system with large dimension. A fast algorithm is ...The computation burden in the model-based predictive control algorithm is heavy when solving QR optimization with a limited sampling step, especially for a complicated system with large dimension. A fast algorithm is proposed in this paper to solve this problem, in which real-time values are modulated to bit streams to simplify the multiplication. In addition, manipulated variables in the prediction horizon are deduced to the current control horizon approximately by a recursive relation to decrease the dimension of QR optimization. The simulation results demonstrate the feasibility of this fast algorithm for MIMO systems.展开更多
To solve the problem of time-awarc test case prioritization,a hybrid algorithm composed of integer linear programming and the genetic algorithm(ILP-GA)is proposed.First,the test case suite which cm maximize the number...To solve the problem of time-awarc test case prioritization,a hybrid algorithm composed of integer linear programming and the genetic algorithm(ILP-GA)is proposed.First,the test case suite which cm maximize the number of covered program entities a d satisfy time constraints is selected by integer linea progamming.Secondly,the individual is encoded according to the cover matrices of entities,and the coverage rate of program entities is used as the fitness function and the genetic algorithm is used to prioritize the selected test cases.Five typical open source projects are selected as benchmark programs.Branch and method are selected as program entities,and time constraint percentages a e 25%and 75%.The experimental results show that the ILP-GA convergence has faster speed and better stability than ILP-additional and IP-total in most cases,which contributes to the detection of software defects as early as possible and reduces the software testing costs.展开更多
基金supported in part by the Foundation of National Key Laboratory of Uranium Resources Exploration-Mining and Nuclear Remote Sensing under Grant 2024QZ-TD-13in part by the National Natural Science Foundation of China under Grant 42564006+1 种基金in part by the Natural Science Foundation of Jiangxi Province under Grant 20242BAB26051in part by the Open Fund of SINOPEC Key Laboratory of Geophysics,and in part by support the plan of Ganpo Juncai under Grant 20243BCE51012.
摘要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.
基金Supported by the National Natural Science Foundation of China(12101205)the Natural Science Foundation of Heilongjiang Province of China(PL2024A010)。
摘要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.
基金funded by the National Science Fund for Distinguished Young Scholars(Grant No.42225206)the National Key R&D Program of China(Grant No.2020YFC1807200)the National Natural Science Foundation of China(Grant No.42072299).
摘要Conventional empirical equations for estimating undrained shear strength(su)from piezocone penetration test(CPTu)data,without incorporating soil physical properties,often lack the accuracy and robustness required for geotechnical site investigations.This study introduces a hybrid virus colony search(VCS)algorithm that integrates the standard VCS algorithm with a mutation-based search mechanism to develop high-performance XGBoost learning models to address this limitation.A dataset of 372 seismic CPTu and corresponding soil physical properties data from 26 geotechnical projects in JiangsuProvince,China,was collected for model development.Comparative evaluations demonstrate that the proposed hybrid VCS-XGBoost model exhibits superior performance compared to standard meta-heuristic algorithm-based XGBoost models.The results highlight that the consideration of soil physical properties significantly improves the predictive accuracy of su,emphasizing the importance of considering additional soil information beyond CPTu data for accurate suestimation.
基金supported by the National Key R&D Program of China(Grant No.2022YFB3207100)National Natural Science Foundation of China(Grant No.L2424216)Major Program(JD)of Hubei Province(Grant No.2023BAA008).
摘要Wafer probe testing is essential for evaluating the reliability of microelectronic devices.As device dimensions continue to shrink,the mechanical stress at the probe tip increases the risk of failure occurring in the brittle dielectric layer.Existing studies usually simplify the plastic behavior of bond pads in finite element(FE)models,making it difficult to accurately predict the stress in the dielectric layer.In this study,the FE model for wafer probe testing was improved by implanting the true plastic properties of Al-(4 wt.%)Cu bond pads obtained from nanoindentation inverse identification.Specifically,a MATLAB and ABAQUS co-simulation method is employed to inversely obtain the plastic properties of Al-(4 wt.%)Cu bond pads from the nanoindentation load-displacement curve.By comparing different gradient-based optimization algorithms,the Levenberg-Marquardt(LM)algorithm was found to be the most suitable for balancing computational efficiency and accuracy in inverse identification.Moreover,a hybrid optimization strategy combining Gauss-Newton and LM algorithms is proposed to mitigate sensitivity to initial values.The results show that the improved model of wafer probe testing achieves high accuracy in stress prediction.This study provides a high-fidelity approach for mechanical reliability assessment of wafer probe testing.
基金funded by Natural Science Foundation of Fujian Province,grant numbers 2023J01975,2026J0011041,and 2026J0011042Educational research projects of young and middle-aged teachers in Fujian Province,grant number JAT220362Industry-University-Research Project of Longyan Nonferrous Metals Research Institute,grant number PT202502.
摘要Traditional heuristic algorithms often fall into local optima and converge slowly when test case prioritization is addressed in regression testing,making them inadequate for complex real-world scenarios.The Aquila optimizer,a novel metaheuristic algorithm,demonstrates strong global exploration capability but still faces limitations,including insufficient exploitation capability and slow convergence.To overcome these challenges,a multi-strategy improved chaotic Cauchy inverse cumulative distribution Aquila optimizer for test case prioritization is proposed.First,a logistic–sine–cosine composite chaotic mapping is introduced during the initialization phase of the Aquila optimizer to increase population diversity.Second,the mutated random walk strategy is used to improve global exploration,further enhancing the global search ability of the Aquila optimizer.Moreover,during the narrowed exploration and narrowed exploitation phases,the Cauchy inverse cumulative distribution flight replaces the Lévy flight strategy to reallocate individual positions,strengthening individuals’optimization capability and preventing the algorithm from becoming trapped in local optima.Finally,in the later iteration stage,the specular reflection learning strategy is used to perturb the optimal individual positions and improve the Aquila optimizer’s convergence accuracy and comprehensive optimization performance.Five Java projects were selected from the Defects4J benchmark datasets to conduct comparative experiments with the Aquila optimizer and seven other metaheuristic algorithms.The results demonstrate the effectiveness and superiority of the improved algorithm in test case prioritization.It achieves average improvements of approximately 4.96%in the average percentage of fault detection,3.82%in the average percentage of block coverage,and 5.64%in the average percentage of decision coverage,enabling faster coverage of code blocks and branches.The results provide an efficient priority sorting solution for complex regression testing scenarios.
基金Natural Science Foundation of China(42304128 and 42074150)the National Key Research and Development Program of China(2023YFC2906704-5 and 2023YFC370790)+1 种基金the Mount Tai Industry Leading Talent Project Special Fund Support(tscx202312018)the Jinan Science and Technology Innovation Development Plan(Social Livelihood Special Project)(202131001)。
摘要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.
基金supported in part by the National Natural Science Foundation of China under Grant 62331027in part by the National Key Research and Development Program under Grant 2024YFB2907301in part by the Young Elite Scientists Sponsorship Program by China Association for Science and Technology under Grant 2022QNRC001.
摘要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.
基金supported by the National Basic Research Program of China (973 Program) (61320)
摘要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.
基金the National Natural Science Foundation of China(No.61703413).
摘要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).
摘要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.
基金supported by the National Natural Science Foundation of China(50975121)the Project 2009-2007 of the Graduate Innovation Fund of Jilin University
摘要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.
基金supported by the National Natural Science Foundation of China for Distinguished Young Scholars(60525303)Doctoral Foundation of Yanshan University(B243).
摘要Recently,a two-dimensional(2-D)Tsallis entropy thresholding method has been proposed as a new method for image segmentation.But the computation complexity of 2-D Tsallis entropy is very large and becomes an obstacle to real time image processing systems.A fast recursive algorithm for 2-D Tsallis entropy thresholding is proposed.The key variables involved in calculating 2-D Tsallis entropy are written in recursive form.Thus,many repeating calculations are avoided and the computation complexity reduces to O(L2)from O(L4).The effectiveness of the proposed algorithm is illustrated by experimental results.
摘要This paper is dedicated to applying the Fourier amplitude sensitivity test(FAST)method to the problem of mixed extension and inflation of a circular cylindrical tube in the presence of residual stresses.The metafunctions and the Ishigami function are considered in the sensitivity analysis(SA).The effects of the input variables on the output variables are investigated,and the most important parameters of the system under the applied pressure and axial force such as the axial stretch and the azimuthal stretch are determined.
基金the National Natural Science Foundation of China(60431010)
摘要A full-wave analysis of the electromagnetic problem of a three-dimensional(3-D)antenna radiating through a 3-D dielectric radome is preserued.The problem is formulated using the Poggio-Miller-Chang-Harrington-Wu(PMCHW)approach for homogeneous dielectric objects and the electric field integral equation for conducting objects.The integral equations are discretized by the method of moment(MoM),in which the conducting and dielectric surface/interfaces are represented by curvilinear triangular patches and the unknown equivalent electric and magnetic currents are expanded using curvilinear RWG basis functions.The resultant matrix equation is then solved by the multilevel fast multipole algorithm(MLFMA)and fast far-field approximation(FAFFA)is used to further accelerate the computation.The radiation patterns of dipole arrays in the presence of radomes are presented.The numerical results demonstrate the accuracy and versatility of this method.
基金The National High Technology Research and Development Program of China(863Pro-gram)(No.2005AA145110)
摘要A new efficient protocol-proving algorithm was proposed for verifying security protocols. This algorithm is based on the improved authentication tests model, which enhances the original model by formalizing the message reply attack. With exact causal dependency relations between messages in this model, the protocol-proving algorithm can avoid the state explosion caused by asynchronous. In order to get the straight proof of security protocols, three authentication theorems are exploited for evaluating the agreement and distinction properties. When the algorithm terminates, it outputs either the proof results or the potential flaws of the security protocol. The experiment shows that the protocol-proving algorithm can detect the type flaw attack on Neuman-Stubblebine protocol, and prove the correctness of NSL protocol by exploring only 10 states.
摘要A general and efficient parallel approach is proposed for the first time to parallelize the hybrid finiteelement-boundary-integral-multi-level fast multipole algorithm(FE-BI-MLFMA).Among many algorithms of FE-BI-MLFMA,the decomposition algorithm(DA)is chosen as a basis for the parallelization of FE-BI-MLFMA because of its distinct numerical characteristics suitable for parallelization.On the basis of the DA,the parallelization of FE-BI-MLFMA is carried out by employing the parallelized multi-frontal method for the matrix from the finiteelement method and the parallelized MLFMA for the matrix from the boundary integral method respectively.The programming and numerical experiments of the proposed parallel approach are carried out in the high perfor-mance computing platform CEMS-Liuhui.Numerical experiments demonstrate that FE-BI-MLFMA is efficiently parallelized and its computational capacity is greatly improved without losing accuracy,efficiency,and generality.
基金Supported by the National Natural Science Foundation of China(61333010,61203157)the Fundamental Research Funds for the Central Universities+2 种基金the National High-Tech Research and Development Program of China(2013AA040701)Shanghai Natural Science Foundation Project(15ZR1408900)Shanghai Key Technologies R&D Program Project(13111103800)
摘要The computation burden in the model-based predictive control algorithm is heavy when solving QR optimization with a limited sampling step, especially for a complicated system with large dimension. A fast algorithm is proposed in this paper to solve this problem, in which real-time values are modulated to bit streams to simplify the multiplication. In addition, manipulated variables in the prediction horizon are deduced to the current control horizon approximately by a recursive relation to decrease the dimension of QR optimization. The simulation results demonstrate the feasibility of this fast algorithm for MIMO systems.
基金The Natural Science Foundation of Education Ministry of Shaanxi Province(No.15JK1672)the Industrial Research Project of Shaanxi Province(No.2017GY-092)Special Fund for Key Discipline Construction of General Institutions of Higher Education in Shaanxi Province
摘要To solve the problem of time-awarc test case prioritization,a hybrid algorithm composed of integer linear programming and the genetic algorithm(ILP-GA)is proposed.First,the test case suite which cm maximize the number of covered program entities a d satisfy time constraints is selected by integer linea progamming.Secondly,the individual is encoded according to the cover matrices of entities,and the coverage rate of program entities is used as the fitness function and the genetic algorithm is used to prioritize the selected test cases.Five typical open source projects are selected as benchmark programs.Branch and method are selected as program entities,and time constraint percentages a e 25%and 75%.The experimental results show that the ILP-GA convergence has faster speed and better stability than ILP-additional and IP-total in most cases,which contributes to the detection of software defects as early as possible and reduces the software testing costs.