期刊文献+
任意字段
题名或关键词
题名
关键词
摘要
作者
第一作者
机构
刊名
分类号
参考文献
作者简介
基金资助
栏目信息
共找到2,009篇文章
< 1 2 … 101 >
每页显示 20 50 100
已选0条
引用分析
参考文献
引证文献
 统计分析
检索结果
已选文献
显示方式：
Improving ENUM-Sieve Reduction Algorithm for Prime Cyclotomic Lattices 认领 引用
1
作者 Kazutaka Toda Yuntao Wang +1 位作者 Hyungrok Jo Yang Li 《Computer Modeling in Engineering & Sciences》 SCIE EI 2026年第7期1406-1426,共21页
The rapid evolution of quantum computing poses a fundamental challenge to classical public-key cryptosystems,accelerating the adoption of lattice-based post-quantum cryptography in large-scale digital infrastructures,... The rapid evolution of quantum computing poses a fundamental challenge to classical public-key cryptosystems,accelerating the adoption of lattice-based post-quantum cryptography in large-scale digital infrastructures,including Future Mobile Internet Technologies(FMIT)and their convergence applications(FMIT-CA).As lattice-based cryptography is expected to play an important role in such environments,accurate hardness estimation and parameter assessment of underlying lattice problems have become increasingly important.Since the security of these cryptographic schemes is closely related to the computational hardness of the Shortest Vector Problem(SVP),improving practical SVP-solving techniques contributes indirectly to the security evaluation of such systems.Among practical SVP solvers,sieve-based approaches such as the General Sieve Kernel(G6K)achieve state-of-the-art performance,yet their exponential complexity and resource demands constrain scalability in high-dimensional settings.In this work,we propose an improved version of the hybrid algorithm ENUM-Sieve Reduction(ESR)proposed by Toda et al.in ProvSec 2025.We refer to our proposal as ENUM-Sieve Reduction 2.0(ESR 2.0).It integrates Block Korkine-Zolotarev 2.0(BKZ 2.0)and extreme-pruning enumeration into the reduction pipeline and introduces a unimodular-matrix-based strategy for partial basis generation.Experimental results suggest that these enhancements enable stronger parameter configurations and more efficient execution in higher dimensions under realistic computational constraints.Experimental evaluations on prime cyclotomic ideal lattices demonstrate the practical usefulness of ESR 2.0 produces vectors equal to or shorter than those obtained by G6K in 75%of the tested instances for dimensions ranging from 96 to 130.Compared with ESR,ESR 2.0 achieves the same or shorter vectors in 62.5%of the tested instances.Although ESR 2.0 requires longer CPU time due to additional enumeration steps,GPU time and peak memory usage remain comparable to those of G6K and ESR.Furthermore,ESR 2.0 renewed record norms in the TU Darmstadt Ideal Lattice Challenge for dimensions 112,126,136,148 and 156.These results indicate the usability of ESR 2.0,providing a competitive and practical framework for high-dimensional SVP solving.The proposed improvements contribute to a more accurate assessment of lattice hardness,which is essential for secure parameter selection in post-quantum cryptographic systems supporting future mobile and converged digital environments. 展开更多
关键词 Post-quantum cryptography ideal lattice shortest vector problem sieve algorithms ENUM-sieve reduction
暂未订购 下载PDF
Optimized VMD algorithm for noise reduction of absorption spectra of CO2 认领 引用
2
作者 Ru Zhang Junfen Wang +3 位作者 Xuemei Shi Mingliang Li Zhanmin Zhao Han Wang 《Optoelectronics Letters》 EI 2026年第1期23-28,共6页
The end tidal carbon dioxide(EtCO2)is crucial for monitoring patients respiratory function,which reflects the status of lung ventilation and gas exchange.Therefore,achieving accurate measurements of EtCO2holds s... The end tidal carbon dioxide(EtCO2)is crucial for monitoring patients respiratory function,which reflects the status of lung ventilation and gas exchange.Therefore,achieving accurate measurements of EtCO2holds significant importance in clinical practice.The measurements of EtCO2based on wavelength modulation-direct absorption spectroscopy(WM-DAS)had great advantages and the noise reduction of spectrum was very important.An optimized variational mode decomposition(VMD)algorithm improved by the dung beetle optimization algorithm and wavelet packet denoising algorithm was proposed to enhance the measurement accuracy of EtCO2concentration.The dung beetle optimization algorithm was used to obtain the optimal number of decomposition mode layers K and secondary penalty factorα.The optimal parameters were used to decompose the original transmitted light intensity signal with noise,and a series of intrinsic mode functions(IMFs)were obtained.Pearson correlation coefficient(R)was used to select the pure signal and the noisy signal,and the noisy signal was denoised by wavelet packet denoising algorithm.The transmitted light intensity signal was reconstructed by the signal processed by wavelet packet denoising algorithm and the pure signal.The results showed that the proposed algorithm could effectively remove the noise of signal of transmitted light intensity and improve the accuracy of concentration measurements of EtCO2. 展开更多
关键词 monitoring patients respiratory functionwhich Variational Mode Decomposition Wavelet Packet Denoising noise reduction spectrum end tidal carbon dioxide etco Dung Beetle Optimization Algorithm dung be lung ventilation
暂未订购 下载PDF
Cooperative Metaheuristics with Dynamic Dimension Reduction for High-Dimensional Optimization Problems 认领 引用
3
作者 Junxiang Li Zhipeng Dong +2 位作者 Ben Han Jianqiao Chen Xinxin Zhang 《Computers, Materials & Continua》 SCIE EI 2026年第1期1484-1502,共19页
Owing to their global search capabilities and gradient-free operation,metaheuristic algorithms are widely applied to a wide range of optimization problems.However,their computational demands become prohibitive when ta... Owing to their global search capabilities and gradient-free operation,metaheuristic algorithms are widely applied to a wide range of optimization problems.However,their computational demands become prohibitive when tackling high-dimensional optimization challenges.To effectively address these challenges,this study introduces cooperative metaheuristics integrating dynamic dimension reduction(DR).Building upon particle swarm optimization(PSO)and differential evolution(DE),the proposed cooperative methods C-PSO and C-DE are developed.In the proposed methods,the modified principal components analysis(PCA)is utilized to reduce the dimension of design variables,thereby decreasing computational costs.The dynamic DR strategy implements periodic execution of modified PCA after a fixed number of iterations,resulting in the important dimensions being dynamically identified.Compared with the static one,the dynamic DR strategy can achieve precise identification of important dimensions,thereby enabling accelerated convergence toward optimal solutions.Furthermore,the influence of cumulative contribution rate thresholds on optimization problems with different dimensions is investigated.Metaheuristic algorithms(PSO,DE)and cooperative metaheuristics(C-PSO,C-DE)are examined by 15 benchmark functions and two engineering design problems(speed reducer and composite pressure vessel).Comparative results demonstrate that the cooperative methods achieve significantly superior performance compared to standard methods in both solution accuracy and computational efficiency.Compared to standard metaheuristic algorithms,cooperative metaheuristics achieve a reduction in computational cost of at least 40%.The cooperative metaheuristics can be effectively used to tackle both high-dimensional unconstrained and constrained optimization problems. 展开更多
关键词 Dimension reduction modified principal components analysis high-dimensional optimization problems cooperative metaheuristics metaheuristic algorithms
暂未订购 下载PDF
Dirichlet-Neumann alternating algorithm for an anisotropic quasi-linear problem in an unbounded domain with a concave angle 认领 引用
4
作者 LIU Bao-qing TU Ming-yue 《Applied Mathematics(A Journal of Chinese Universities)》 SCIE CSCD 2026年第2期401-416,共16页
In this paper,based on the Kirchhoff transformation and the natural boundary reduction,a Dirichlet-Neumann(D-N)alternating algorithm is discussed for solving the anisotropic quasi-linear problem in an unbounded domain... In this paper,based on the Kirchhoff transformation and the natural boundary reduction,a Dirichlet-Neumann(D-N)alternating algorithm is discussed for solving the anisotropic quasi-linear problem in an unbounded domain with a concave angle.By using the principle of the natural boundary reduction,the natural integral equation on the elliptical arc artificial boundary is obtained in this paper,and the convergence of the algorithm and analysis is proved.Meanwhile,the convergence rate for a typical domain is given in detail.Finally,some numerical examples are verified to show the feasibility of the method. 展开更多
关键词 anisotropic quasi-linear problem D-N alternating algorithm natural boundary reduction
暂未订购 下载PDF
Weighted k-NNC:An Efficient Computation Reduction Method for Metaheuristic-Based Structural Optimization 认领 引用
5
作者 Anh-Vu Nguyen Tien-Chuong Vu +2 位作者 Ba-Duan Nguyen Hoang-Anh Pham Ravipudi Venkata Rao 《Computer Modeling in Engineering & Sciences》 SCIE EI 2026年第4期455-487,共33页
Structural optimization is essential for finding optimal designs in practical engineering tasks.Metaheuristic algorithms have been widely applied in structural optimization problems in recent years,especially when dea... Structural optimization is essential for finding optimal designs in practical engineering tasks.Metaheuristic algorithms have been widely applied in structural optimization problems in recent years,especially when dealing with discrete design variables,the nonlinearity of the objective function and constraints.Unlike gradientbased algorithms,which rely on the slope variation of a function,metaheuristic algorithms do not require derivative calculations and thus avoid being trapped in local optimum.However,metaheuristic algorithms often require numerous function evaluations,involving costly structural analyses,thus increasing computational load considerably.This paper investigates a method to reduce computational load,specifically by reducing the number of function evaluations for metaheuristic-based structural optimization problems.The proposed strategy is based on eliminating unpromising designs during the optimization process.For each newly generated solution,an early assessment through its k nearest neighbors,named k-nearest neighbor comparison(k-NNC),is applied,acting as a filter.If a solution is deemed less promising,it is eliminated without going through the function evaluation step.Conversely,if a solution is deemed good,it is retained for the next comparison and selection step.This paper presents the implementation sequence of k-NNC,highlighting its disadvantages in terms of efficiency and accuracy.From this,a new method,the distance-weighted k-nearest neighbor comparison(wkNNC),has been developed.In wkNNC,the distance from the k neighbors to the solution under consideration is used as the weight for comparison.Furthermore,an archive of infeasible solutions and the potential solution refinement are introduced for enhancing the accuracy and efficiency of wkNNC.The superiority of wkNNC is demonstrated in the sizing optimization of some benchmark discrete cross-section truss structures.The wkNNC method,combined with the Best-Worst-Random(BWR)algorithm,achieves a computational load reduction of over 80 percent. 展开更多
关键词 Structural optimization metaheuristic algorithm computation reduction k-NN distance-weighted k-NNC BWR algorithm
暂未订购 下载PDF
A fast algorithm for solving the scattering problem from an open rectangular cavity 认领 引用
6
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
暂未订购 下载PDF
Enhanced minimum attribute reduction based on quantum-inspired shuffled frog leaping algorithm 认领 引用 被引量：6
7
作者 Weiping Ding Jiandong Wang +1 位作者 Zhijin Guan Quan Shi 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2013年第3期426-434,共9页
Attribute reduction in the rough set theory is an important feature selection method, but finding a minimum attribute reduction has been proven to be a non-deterministic polynomial （NP）-hard problem. Therefore, it i... Attribute reduction in the rough set theory is an important feature selection method, but finding a minimum attribute reduction has been proven to be a non-deterministic polynomial （NP）-hard problem. Therefore, it is necessary to investigate some fast and effective approximate algorithms. A novel and enhanced quantum-inspired shuffled frog leaping based minimum attribute reduction algorithm （QSFLAR） is proposed. Evolutionary frogs are represented by multi-state quantum bits, and both quantum rotation gate and quantum mutation operators are used to exploit the mechanisms of frog population diversity and convergence to the global optimum. The decomposed attribute subsets are co-evolved by the elitist frogs with a quantum-inspired shuffled frog leaping algorithm. The experimental results validate the better feasibility and effectiveness of QSFLAR, comparing with some representa- tive algorithms. Therefore, QSFLAR can be considered as a more competitive algorithm on the efficiency and accuracy for minimum attribute reduction. 展开更多
关键词 minimum attribute reduction quantum-inspired shuf- fled frog leaping algorithm multi-state quantum bit quantum rotation gate and quantum mutation elitist frog.
暂未订购 下载PDF
New Multi-Channel VSMFxLMS Algorithm for Vibration Reduction of Gear Systems 认领 引用 被引量：1
8
作者 Zhibo Geng Min Chen +2 位作者 Yingjian Wang Yun Kong Ke Xiao 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2024年第5期233-247,共15页
At present,the active control of gear vibration mostly relies on existing algorithms.In order to achieve effective vibration reduction of the gear system,particularly during the vibration process,this paper proposes a... At present,the active control of gear vibration mostly relies on existing algorithms.In order to achieve effective vibration reduction of the gear system,particularly during the vibration process,this paper proposes a multi-channel VSMFxLMS algorithm based on the FxLMS algorithm.This novel approach takes into account the time-varying nature of the vibration signal during gear vibration.Adaptive filter power coefficients are updated in a skip-tongue variable-step manner using momentum factors.Firstly,the paper establishes the dynamics model of the gear system and analyzes the nonlinear dynamic characteristics of the system.It then examines the vibration damping effect of the FxLMS algorithm and analyzes its performance under different gear system motion states,considering different step lengths and momentum factors.Lastly,the proposed VSMFxLMS algorithm is compared with the FxLMS algorithm,highlighting the superiority of the former.Overall,this research highlights the potential of a multi-channel VSMFxLMS algorithm in reducing vibrations in gear systems.The study optimizes the performance of gear systems while using advanced control strategies. 展开更多
关键词 Vibration reduction Gear system FxLMS algorithm Multi-channel VSMFxLMS algorithm
暂未订购 下载PDF
Dynamic self-adaptive ANP algorithm and its application to electric field simulation of aluminum reduction cell 认领 引用 被引量：2
9
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)
暂未订购 下载PDF
Fuzzy-GA based algorithm for optimal placement and sizing of distribution static compensator (DSTATCOM) for loss reduction of distribution network considering reconfiguration 认领 引用 被引量：1
10
作者 Mohammad Mohammadi Mahyar Abasi A.Mohammadi Rozbahani 《Journal of Central South University》 SCIE EI CAS CSCD 2017年第2期245-258,共14页
This work presents a fuzzy based methodology for distribution system feeder reconfiguration considering DSTATCOM with an objective of minimizing real power loss and operating cost. Installation costs of DSTATCOM devic... This work presents a fuzzy based methodology for distribution system feeder reconfiguration considering DSTATCOM with an objective of minimizing real power loss and operating cost. Installation costs of DSTATCOM devices and the cost of system operation, namely, energy loss cost due to both reconfiguration and DSTATCOM placement, are combined to form the objective function to be minimized. The distribution system tie switches, DSTATCOM location and size have been optimally determined to obtain an appropriate operational condition. In the proposed approach, the fuzzy membership function of loss sensitivity is used for the selection of weak nodes in the power system for the placement of DSTATCOM and the optimal parameter settings of the DFACTS device along with optimal selection of tie switches in reconfiguration process are governed by genetic algorithm(GA). Simulation results on IEEE 33-bus and IEEE 69-bus test systems concluded that the combinatorial method using DSTATCOM and reconfiguration is preferable to reduce power losses to 34.44% for 33-bus system and to 45.43% for 69-bus system. 展开更多
关键词 distribution FACTS （DFACTS） distribution static compensator （DSTATCOM） network reconfiguration genetic algorithm fuzzy membership function power loss reduction
暂未订购 下载PDF
Attribute reduction algorithm based on discernibility for decision table 认领 引用 被引量：1
11
作者 曾凡智 卢炎生 黄国顺 《Journal of Shanghai University(English Edition)》 2008年第6期531-536,共6页
The attribute reduction algorithms of decision table based on discernible matrix are required to construct discernible matrix, which reduces efficiency of algorithms. In this paper, the relationship between attribute ... The attribute reduction algorithms of decision table based on discernible matrix are required to construct discernible matrix, which reduces efficiency of algorithms. In this paper, the relationship between attribute discernible matrix and its discernibility is first established for general information systems. Based on the idea that the equivalent discernible matrix has a same attribute reduction, existing matrices are modified and a formula of attribute discernibility associated with algebraic reduction for decision table is proposed. A heuristic attribute reduction algorithm based on attribute discernibility is presented. Experimental results indicate that the algorithm can more easily explore an optimal or sub-optimal reduction, and is efficient. 展开更多
关键词 decision table attribute reduction discernibility discernible matrix algorithm
暂未订购 下载PDF
ARNOLDI REDUCTION ALGORITHM FOR LARGE SCALE GYROSCOPIC EIGENVALUE PROBLEM 认领 引用
12
作者 Zheng Zhaochang Ren Gexue, Department of Engineering Mechanics, Tsinghua University, Beijing 100084 《Acta Mechanica Solida Sinica》 SCIE 1996年第2期95-103,共9页
Based on Arnoldi's method, a version of generalized Arnoldi algorithm has been developed for the reduction of gyroscopic eigenvalue problems. By utilizing the skew symmetry of system matrix, a very simple recurren... Based on Arnoldi's method, a version of generalized Arnoldi algorithm has been developed for the reduction of gyroscopic eigenvalue problems. By utilizing the skew symmetry of system matrix, a very simple recurrence scheme, named gyroscopic Arnoldi reduction algorithm has been obtained, which is even simpler than the Lanczos algorithm for symmetric eigenvalue problems. The complex number computation is completely avoided. A restart technique is used to enable the reduction algorithm to have iterative characteristics. It has been found that the restart technique is not only effective for the convergence of multiple eigenvalues but it also furnishes the reduction algorithm with a technique to check and compute missed eigenvalues. By combining it with the restart technique, the algorithm is made practical for large-scale gyroscopic eigenvalue problems. Numerical examples are given to demonstrate the effectiveness of the method proposed. 展开更多
关键词 gyroscopic eigenvalue problem skew symmetry Arnoldi reduction algorithm restart technique
暂未订购 下载PDF
A POTENTIAL REDUCTION ALGORITHM FOR LINEARLY CONSTRAINED CONVEX PROGRAMMING 认领 引用
13
作者 Liang XimingCollege of Information Science & Engineering,Central South Univ.,Changsha 410083. 《Applied Mathematics(A Journal of Chinese Universities)》 2001年第4期439-445,共7页
A potential reduction algorithm is proposed for optimization of a convex function subject to linear constraints.At each step of the algorithm,a system of linear equations is solved to get a search direction and the Ar... A potential reduction algorithm is proposed for optimization of a convex function subject to linear constraints.At each step of the algorithm,a system of linear equations is solved to get a search direction and the Armijo's rule is used to determine a stepsize.It is proved that the algorithm is globally convergent.Computational results are reported. 展开更多
关键词 Potential reduction algorithm linearly constrained convex programming global convergence numerical experiments.
暂未订购 下载PDF
Structural damage detection based on model reduction and response reconstruction 认领 引用
14
作者 ZOU Yun-feng SU Yun-hui +2 位作者 LU Xuan-dong HE Xu-hui CAI Chen-zhi 《Journal of Central South University》 SCIE EI CAS CSCD 2025年第11期4439-4462,共24页
Structural damage detection is hard to conduct in large-scale civil structures due to enormous structural data and insufficient damage features.To improve this situation,a damage detection method based on model reduct... Structural damage detection is hard to conduct in large-scale civil structures due to enormous structural data and insufficient damage features.To improve this situation,a damage detection method based on model reduction and response reconstruction is presented.Based on the framework of two-step model updating including substructure-level localization and element-level detection,the response reconstruction strategy with an improved sensitivity algorithm is presented to conveniently complement modal information and promote the reliability of model updating.In the iteration process,the reconstructed response is involved in the sensitivity algorithm as a reconstruction-related item.Besides,model reduction is applied to reduce computational degrees of freedom(DOFs)in each detection step.A numerical truss bridge is modelled to vindicate the effectiveness and efficiency of the method.The results showed that the presented method reduces the requirement for installed sensors while improving efficiency and ensuring accuracy of damage detection compared to traditional methods. 展开更多
关键词 damage detection model reduction response reconstruction two-step model updating sensitivity algorithm
暂未订购 下载PDF
Dynamic Multi-Objective Gannet Optimization(DMGO):An Adaptive Algorithm for Efficient Data Replication in Cloud Systems 认领 引用
15
作者 P.William Ved Prakash Mishra +3 位作者 Osamah Ibrahim Khalaf Arvind Mukundan Yogeesh N Riya Karmakar 《Computers, Materials & Continua》 SCIE EI 2025年第9期5133-5156,共24页
Cloud computing has become an essential technology for the management and processing of large datasets,offering scalability,high availability,and fault tolerance.However,optimizing data replication across multiple dat... Cloud computing has become an essential technology for the management and processing of large datasets,offering scalability,high availability,and fault tolerance.However,optimizing data replication across multiple data centers poses a significant challenge,especially when balancing opposing goals such as latency,storage costs,energy consumption,and network efficiency.This study introduces a novel Dynamic Optimization Algorithm called Dynamic Multi-Objective Gannet Optimization(DMGO),designed to enhance data replication efficiency in cloud environments.Unlike traditional static replication systems,DMGO adapts dynamically to variations in network conditions,system demand,and resource availability.The approach utilizes multi-objective optimization approaches to efficiently balance data access latency,storage efficiency,and operational costs.DMGO consistently evaluates data center performance and adjusts replication algorithms in real time to guarantee optimal system efficiency.Experimental evaluations conducted in a simulated cloud environment demonstrate that DMGO significantly outperforms conventional static algorithms,achieving faster data access,lower storage overhead,reduced energy consumption,and improved scalability.The proposed methodology offers a robust and adaptable solution for modern cloud systems,ensuring efficient resource consumption while maintaining high performance. 展开更多
关键词 Cloud computing data replication dynamic optimization multi-objective optimization gannet optimization algorithm adaptive algorithms resource efficiency scalability latency reduction energy-efficient computing
暂未订购 下载PDF
Model reduction using the genetic algorithmand routh approxi mations 认领 引用
16
作者 李红星 芦金石 闫红书 《Journal of Systems Engineering and Electronics》 2005年第3期632-639,共8页
A new method of model reduction combining the genetic algorithm（GA） with the Routh approximation method is presented. It is suggested that a high-order system can be approximated by a low-order model with a time del... A new method of model reduction combining the genetic algorithm（GA） with the Routh approximation method is presented. It is suggested that a high-order system can be approximated by a low-order model with a time delay. The denominator parameters of the reduced-order model are determined by the Routh approximation method, then the numerator parameters and time delay are identified by the GAL. The reduced-order models obtained by the proposed method will always be stable if the original system is stable and produce a good approximation to the original system in both the frequency domain and time domain. Two numerical examples show that the method is cornputationally simple and efficient. 展开更多
关键词 model reduction time delay genetic algorithm Routh approximation.
暂未订购 下载PDF
Nonparametric Regression Algorithm for Short-term Traffic Flow Forecasting Based on Data Reduction and Support Vector Machine 认领 引用
17
作者 WU Jin-wu ZHANG Hai-feng RAN Xu-dong 《Journal of Highway and Transportation Research and Development(English Edition)》 2020年第3期96-103,共8页
Nonparametric regression is an important method for short-term traffic flow forecasting,but the traditional nonparametric regression method needs a large storage space and slow query speed when the data are large and ... Nonparametric regression is an important method for short-term traffic flow forecasting,but the traditional nonparametric regression method needs a large storage space and slow query speed when the data are large and the dimension is high.In this paper,an improved nonparametric regression traffic flow forecasting algorithm is proposed.Subtraction fuzzy clustering method is used to cluster historical data to reduce the amount of data in the pattern database.Principal component analysis(PCA)is used to reduce the dimension of the pattern to overcome the problems of slow matching speed and interference of irrelevant dimension caused by the high dimension of the pattern.The support vector machine method is used to estimate the value of the final predicted variables by searching the patterns.The operation efficiency and prediction accuracy of the algorithm are improved.An online simulation-based test shows that the algorithm exhibits better efficiency and accuracy compared with traditional methods. 展开更多
关键词 ITS short-term traffic flow forecasting nonparametric regression algorithm data reduction intelligent transport
暂未订购 下载PDF
Integrating Variable Reduction Strategy With Evolutionary Algorithms for Solving Nonlinear Equations Systems 认领 引用 被引量：1
18
作者 Aijuan Song Guohua Wu +1 位作者 Witold Pedrycz Ling Wang 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2022年第1期75-89,共15页
Nonlinear equations systems(NESs)are widely used in real-world problems and they are difficult to solve due to their nonlinearity and multiple roots.Evolutionary algorithms(EAs)are one of the methods for solving NESs,... Nonlinear equations systems(NESs)are widely used in real-world problems and they are difficult to solve due to their nonlinearity and multiple roots.Evolutionary algorithms(EAs)are one of the methods for solving NESs,given their global search capabilities and ability to locate multiple roots of a NES simultaneously within one run.Currently,the majority of research on using EAs to solve NESs focuses on transformation techniques and improving the performance of the used EAs.By contrast,problem domain knowledge of NESs is investigated in this study,where we propose the incorporation of a variable reduction strategy(VRS)into EAs to solve NESs.The VRS makes full use of the systems of expressing a NES and uses some variables(i.e.,core variable)to represent other variables(i.e.,reduced variables)through variable relationships that exist in the equation systems.It enables the reduction of partial variables and equations and shrinks the decision space,thereby reducing the complexity of the problem and improving the search efficiency of the EAs.To test the effectiveness of VRS in dealing with NESs,this paper mainly integrates the VRS into two existing state-of-the-art EA methods(i.e.,MONES and DR-JADE)according to the integration framework of the VRS and EA,respectively.Experimental results show that,with the assistance of the VRS,the EA methods can produce better results than the original methods and other compared methods.Furthermore,extensive experiments regarding the influence of different reduction schemes and EAs substantiate that a better EA for solving a NES with more reduced variables tends to provide better performance. 展开更多
关键词 Evolutionary algorithm(EA) nonlinear equations systems(ENSs) problem domain knowledge variable reduction strategy(VRS)
暂未订购 下载PDF
A projection-domain iterative algorithm for metal artifact reduction by minimizing the total-variation norm and the negative-pixel energy 认领 引用 被引量：2
19
作者 Gengsheng L.Zeng 《Visual Computing for Industry,Biomedicine,and Art》 EI 2022年第1期1-11,共11页
Metal objects in X-ray computed tomography can cause severe artifacts.The state-of-the-art metal artifact reduction methods are in the sinogram inpainting category and are iterative methods.This paper proposes a proje... Metal objects in X-ray computed tomography can cause severe artifacts.The state-of-the-art metal artifact reduction methods are in the sinogram inpainting category and are iterative methods.This paper proposes a projectiondomain algorithm to reduce the metal artifacts.In this algorithm,the unknowns are the metal-affected projections,while the objective function is set up in the image domain.The data fidelity term is not utilized in the objective function.The objective function of the proposed algorithm consists of two terms:the total variation of the metalremoved image and the energy of the negative-valued pixels in the image.After the metal-affected projections are modified,the final image is reconstructed via the filtered backprojection algorithm.The feasibility of the proposed algorithm has been verified by real experimental data. 展开更多
关键词 Analytical image reconstruction Metal artifact reduction Projection-domain iterative algorithm X-ray computed tomography
暂未订购 下载PDF
Stable Model Order Reduction Method for Fractional-Order Systems Based on Unsymmetric Lanczos Algorithm 认领 引用 被引量：1
20
作者 Zhe Gao 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2019年第2期485-492,共8页
This study explores a stable model order reduction method for fractional-order systems. Using the unsymmetric Lanczos algorithm, the reduced order system with a certain number of matched moments is generated. To obtai... This study explores a stable model order reduction method for fractional-order systems. Using the unsymmetric Lanczos algorithm, the reduced order system with a certain number of matched moments is generated. To obtain a stable reduced order system, the stable model order reduction procedure is discussed. By the revised operation on the tridiagonal matrix produced by the unsymmetric Lanczos algorithm, we propose a reduced order modeling method for a fractional-order system to achieve a satisfactory fitting effect with the original system by the matched moments in the frequency domain. Besides, the bound function of the order reduction error is offered. Two numerical examples are presented to illustrate the effectiveness of the proposed method. 展开更多
关键词 Fractional-order systems order reduction stable reduced order systems unsymmetric Lanczos algorithm
暂未订购 下载PDF
已选0条
引用分析
参考文献
引证文献
 统计分析
检索结果
已选文献
上一页 1 2 … 101 下一页 到第 页
在线咨询 使用帮助 返回顶部 意见反馈