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An improved Alpha-shape algorithm for extracting section contours of the super-high steel bridge tower using point clouds 认领 引用 被引量：2
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作者 ZHANG Yiming ZHAO Tianhao +2 位作者 LIAO Ruixuan LI Haoqing WANG Hao 《Journal of Southeast University(English Edition)》 EI CAS 2026年第1期26-35,共10页
The virtual preassembly of super-high steel bridge towers faces a challenge in the efficient and precise extraction of complex cross-sectional features.Factors such as fabrication errors,gravity-induced deformations,a... The virtual preassembly of super-high steel bridge towers faces a challenge in the efficient and precise extraction of complex cross-sectional features.Factors such as fabrication errors,gravity-induced deformations,and temperature fluctuations can compromise the accuracy of contour extraction.To address these limitations,an improved Alpha-shape-based point cloud contour extraction method is proposed.The proposed approach uses a hierarchical strategy to process three-dimensional laser scanning point clouds.The processed data are then subjected to curvatureadaptive voxel filtering to reduce acquisition noise.In addition,an enhanced iterative closest point(ICP)variant with correspondence validation accurately aligns the discrete point cloud segments.The proposed curvature-responsive Alpha-shape framework enables multiscale contour delineation through topology-adaptive threshold modulation,which resolves boundary ambiguities in geometrically complex cross-sections.The method was experimentally validated using field-acquired measurement datasets from the Zhangjinggao Yangtze River Bridge tower segments,confirming its capability to reconstruct noncanonical cross-sectional geometries.Three contour extraction methods,including Poisson reconstruction,the conventional Alpha-shape algorithm,and random sample consensus with ICP(RANSAC-ICP),were compared to evaluate the performance of the proposed Alpha-shape algorithm.The results demonstrate that the proposed method achieves superior contour extraction accuracy and data reduction efficiency,highlighting its effectiveness in contour extraction tasks. 展开更多
关键词 super-high steel bridge tower point cloud contour extraction improved Alpha-shape algorithm
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Rock discontinuity extraction from 3D point clouds using pointwise clustering algorithm 认领 引用 被引量：1
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作者 Xiaoyu Yi Wenxuan Wu +2 位作者 Wenkai Feng Yongjian Zhou Jiachen Zhao 《Journal of Rock Mechanics and Geotechnical Engineering》 SCIE CSCD 2025年第7期4429-4444,共16页
Recognizing discontinuities within rock masses is a critical aspect of rock engineering.The development of remote sensing technologies has significantly enhanced the quality and quantity of the point clouds collected ... Recognizing discontinuities within rock masses is a critical aspect of rock engineering.The development of remote sensing technologies has significantly enhanced the quality and quantity of the point clouds collected from rock outcrops.In response,we propose a workflow that balances accuracy and efficiency to extract discontinuities from massive point clouds.The proposed method employs voxel filtering to downsample point clouds,constructs a point cloud topology using K-d trees,utilizes principal component analysis to calculate the point cloud normals,and employs the pointwise clustering(PWC)algorithm to extract discontinuities from rock outcrop point clouds.This method provides information on the location and orientation(dip direction and dip angle)of the discontinuities,and the modified whale optimization algorithm(MWOA)is utilized to identify major discontinuity sets and their average orientations.Performance evaluations based on three real cases demonstrate that the proposed method significantly reduces computational time costs without sacrificing accuracy.In particular,the method yields more reasonable extraction results for discontinuities with certain undulations.The presented approach offers a novel tool for efficiently extracting discontinuities from large-scale point clouds. 展开更多
关键词 Rock mass discontinuity 3D point clouds Pointwise clustering(PWC)algorithm Modified whale optimization algorithm(MWOA)
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Harnessing Trend Theory to Enhance Distributed Proximal Point Algorithm Approaches for Multi-Area Economic Dispatch Optimization 认领 引用
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作者 Yaming Ren Xing Deng 《Computers, Materials & Continua》 SCIE EI 2025年第3期4503-4533,共31页
The exponential growth in the scale of power systems has led to a significant increase in the complexity of dispatch problem resolution,particularly within multi-area interconnected power grids.This complexity necessi... The exponential growth in the scale of power systems has led to a significant increase in the complexity of dispatch problem resolution,particularly within multi-area interconnected power grids.This complexity necessitates the employment of distributed solution methodologies,which are not only essential but also highly desirable.In the realm of computational modelling,the multi-area economic dispatch problem(MAED)can be formulated as a linearly constrained separable convex optimization problem.The proximal point algorithm(PPA)is particularly adept at addressing such mathematical constructs effectively.This study introduces parallel(PPPA)and serial(SPPA)variants of the PPA as distributed algorithms,specifically designed for the computational modelling of the MAED.The PPA introduces a quadratic term into the objective function,which,while potentially complicating the iterative updates of the algorithm,serves to dampen oscillations near the optimal solution,thereby enhancing the convergence characteristics.Furthermore,the convergence efficiency of the PPA is significantly influenced by the parameter c.To address this parameter sensitivity,this research draws on trend theory from stock market analysis to propose trend theory-driven distributed PPPA and SPPA,thereby enhancing the robustness of the computational models.The computational models proposed in this study are anticipated to exhibit superior performance in terms of convergence behaviour,stability,and robustness with respect to parameter selection,potentially outperforming existing methods such as the alternating direction method of multipliers(ADMM)and Auxiliary Problem Principle(APP)in the computational simulation of power system dispatch problems.The simulation results demonstrate that the trend theory-based PPPA,SPPA,ADMM and APP exhibit significant robustness to the initial value of parameter c,and show superior convergence characteristics compared to the residual balancing ADMM. 展开更多
关键词 Multi-area economic dispatch problem proximal point algorithm trend theory
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Structural Reliability Analysis Based on Differential Evolution Algorithm and Hypersphere Integration 认领 引用
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作者 CHEN Zhenzhong HAN Zhuo +4 位作者 WANG Peiyu PAN Qianghua LI Xiaoke GAN Xuehui CHEN Ge 《Journal of Donghua University(English Edition)》 CAS 2026年第1期118-130,共13页
In reliability analyses,the absence of a priori information on the most probable point of failure(MPP)may result in overlooking critical points,thereby leading to biased assessment outcomes.Moreover,second-order relia... In reliability analyses,the absence of a priori information on the most probable point of failure(MPP)may result in overlooking critical points,thereby leading to biased assessment outcomes.Moreover,second-order reliability methods exhibit limited accuracy in highly nonlinear scenarios.To overcome these challenges,a novel reliability analysis strategy based on a multimodal differential evolution algorithm and a hypersphere integration method is proposed.Initially,the penalty function method is employed to reformulate the MPP search problem as a conditionally constrained optimization task.Subsequently,a differential evolution algorithm incorporating a population delineation strategy is utilized to identify all MPPs.Finally,a paraboloid equation is constructed based on the curvature of the limit-state function at the MPPs,and the failure probability of the structure is calculated by using the hypersphere integration method.The localization effectiveness of the MPPs is compared through multiple numerical cases and two engineering examples,with accuracy comparisons of failure probabilities against the first-order reliability method(FORM)and the secondorder reliability method(SORM).The results indicate that the method effectively identifies existing MPPs and achieves higher solution precision. 展开更多
关键词 reliability analysis design point positioning differential evolution algorithm hypersphere integration
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基于改进PointPillar点云检测算法的3D环境感知技术研究 认领 引用
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作者 陈春超 王昊 +2 位作者 周旭日 王立成 石龙 《电子设计工程》 2026年第7期169-174,共6页
针对当前3D环境感知中图像检测准确率低、感知效果差的问题,研究提出了一种基于改进PointPillar点云检测算法的3D环境感知技术。研究对传统PointPillar点云检测算法的特征提取网络进行改进,并引入新的双重注意力机制以提升算法的检测性... 针对当前3D环境感知中图像检测准确率低、感知效果差的问题,研究提出了一种基于改进PointPillar点云检测算法的3D环境感知技术。研究对传统PointPillar点云检测算法的特征提取网络进行改进,并引入新的双重注意力机制以提升算法的检测性能。通过在XYZ数据集上的测试,结果表明,改进算法在静止汽车检测上的准确率高达96.85%,比其他算法提升了19.17%;在不同模块改进时,算法的准确率也显著提升。此外,改进算法的参数量最低只有7235,交并比(IoU)达0.86,表明其检测框与真实目标框的重合度更高。由此可见,该算法在3D环境感知和图像检测中具有更好的效果,检测准确率显著提高,为3D环境感知研究提供了有益的指导。 展开更多
关键词 3D环境 感知 PointPillar点云检测算法 准确率 图像检测
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TWO PARALLEL ALGORITHMS FOR A CLASS OF SPLIT COMMON SOLUTION PROBLEMS 认领 引用
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作者 Truong Minh TUYEN Nguyen Thi TRANG Tran Thi HUONG 《Acta Mathematica Scientia》 SCIE CSCD 2026年第1期505-518,共14页
We study the split common solution problem with multiple output sets for monotone operator equations in Hilbert spaces.To solve this problem,we propose two new parallel algorithms.We establish a weak convergence theor... We study the split common solution problem with multiple output sets for monotone operator equations in Hilbert spaces.To solve this problem,we propose two new parallel algorithms.We establish a weak convergence theorem for the first and a strong convergence theorem for the second. 展开更多
关键词 iterative algorithm Hilbert space metric projection proximal point algorithm
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A differential Lucy-Richardson-Rosen Algorithm for near-diffractionlimited image restoration guided by wavefront sensing 认领 引用
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作者 Lianhui Zheng Zhongjian Gao 《Astronomical Techniques and Instruments》 CSCD 2026年第3期250-259,共10页
The Lucy-Richardson-Rosen Algorithm is widely used for image restoration,but suffers from slow convergence or failure when analyzing images with severe optical aberrations and high noise.To address these limitations,w... The Lucy-Richardson-Rosen Algorithm is widely used for image restoration,but suffers from slow convergence or failure when analyzing images with severe optical aberrations and high noise.To address these limitations,we propose the Differential Lucy-Richardson-Rosen Algorithm which enhances both robustness and convergence speed.By integrating a Hartmann-Shack wavefront sensor into the imaging system,our proposed algorithm directly measures wavefront distortions to accurately estimate the spatially varying point spread function,enabling high-fidelity non-blind deconvolution,even for images acquired by ground-based telescopes,with significant optical imperfections.Extensive simulations and experiments demonstrate that our proposed algorithm outperforms its predecessor in image quality and computational efficiency under challenging aberration and noise conditions.Its rapid and stable performance makes it particularly suitable for real-time or near-real-time astronomical imaging,where reliable,high-resolution recovery is critical.This work advances computational imaging for next-generation astronomical instrumentation through a tightly coupled hardware-algorithm framework. 展开更多
关键词 Image restoration Lucy-Richardson-Rosen Algorithm Wavefront sensing Point Spread Function estimation Astronomical instrumentation
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面向自动驾驶场景的PointPillars目标检测模型INT8量化研究 认领 引用
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作者 吉新宇 韩晋 +2 位作者 刘凌骁 史文馨 刘彦炜 《汽车实用技术》 2026年第16期22-27,共6页
针对自动驾驶场景下3D点云检测算法的实时性需求,INT8量化是主流轻量化方案,但传统图像领域量化方法在点云算法上存在精度骤降问题。以PointPillars算法为研究对象,通过量化敏感层分析发现,Pillar特征提取网络(PFN)是量化精度损失的核... 针对自动驾驶场景下3D点云检测算法的实时性需求,INT8量化是主流轻量化方案,但传统图像领域量化方法在点云算法上存在精度骤降问题。以PointPillars算法为研究对象,通过量化敏感层分析发现,Pillar特征提取网络(PFN)是量化精度损失的核心瓶颈,其输入激活值呈现动态范围差异大、离群值多的分布特性。借鉴大模型分布优化思路,提出在PFN层输入端引入均方根层归一化(RMSNorm)并进行微调,将特征动态范围压缩至INT8量化友好区间。实验表明,该方法在NuScenes数据集上使PointPillars模型INT8量化后的平均精度均值(mAP)损失从13.7%降至1.4%,推理速度提升3.1倍,模型体积压缩75%;且该方案在CenterPoint算法上同样有效,mAP损失控制在1.8%以内。研究为3D点云检测模型的高效量化提供了可行路径,也为超低比特量化奠定基础。 展开更多
关键词 3D点云检测 PointPillars算法 INT8量化 后训练量化 RMSNorm 自动驾驶
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A study on the dynamic tie points ASI algorithm in the Arctic Ocean 认领 引用 被引量：13
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作者 HAO Guanghua SU Jie 《Acta Oceanologica Sinica》 SCIE CAS CSCD 2015年第11期126-135,共10页
Sea ice concentration is an important parameter for polar sea ice monitoring. Based on 89 GHz AMSR-E （Advanced Microwave Scanning Radiometer for Earth Observing System） data, a gridded high-resolution passive microw... Sea ice concentration is an important parameter for polar sea ice monitoring. Based on 89 GHz AMSR-E （Advanced Microwave Scanning Radiometer for Earth Observing System） data, a gridded high-resolution passive microwave sea ice concentration product can be obtained using the ASI （the Arctic Radiation And Turbulence Interaction Study （ARTIST） Sea Ice） retrieval algorithm. Instead of using fixed-point values, we developed ASi algorithm based on daily changed tie points, called as the dynamic tie point ASI algorithm in this study. Here the tie points are expressed as the brightness temperature polarization difference of open water and 100% sea ice. In 2010, the yearly-averaged tie points of open water and sea ice in Arctic are estimated to be 50.8 K and 7.8 K, respectively. It is confirmed that the sea ice concentrations retrieved by the dynamic tie point ASI algorithm can increase （decrease） the sea ice concentrations in low-value （high-value） areas. This improved the sea ice concentrations by present retrieval algorithm from microwave data to some extent. Comparing with the products using fixed tie points, the sea ice concentrations retrieved from AMSR-E data by using the dynamic tie point ASI algorithm are closer to those obtained from MODIS （Moderate-resolution Imaging Spectroradiometer） data. In 40 selected cloud-free sample regions, 95% of our results have smaller mean differences and 75% of our results have lower root mean square （RMS） differences compare with those by the fixed tie points. 展开更多
关键词 dynamic tie points ASI algorithm sea ice concentration AMSR-E MODIS
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PLC-Oriented Access Point Location Planning Algorithm in Smart-Grid Communication Networks 认领 引用 被引量：3
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作者 Ningzhe Xing Sidong Zhang +1 位作者 Yue Shi Shaoyong Guo 《China Communications》 SCIE CSCD 2016年第9期91-102,共12页
In this study, we investigate the optimal location of access points （APs） to connect end nodes with a service provider through power-line communication in smartgrid communication networks. APs are the gateways of po... In this study, we investigate the optimal location of access points （APs） to connect end nodes with a service provider through power-line communication in smartgrid communication networks. APs are the gateways of power-distribution communication networks, connecting users to control centers. Hence, they are vital for the reliable, safe, and economical operation of a power system. This paper proposes a planning method for AP allocation that takes into consideration economics, reliability, network delay, and （n-l） resilience. First, an optimization model for the AP location is established, which minimizes the cost of installing APs, while satisfying the reliability, network delay, and （n-1） resilience constraints. Then, an improved genetic algorithm is proposed to solve the optimization problem. The simulation results indicate that the proposed planning method can deal with diverse network conditions satisfactorily. Furthermore, it can be applied effectively with high flexibility and scalability. 展开更多
关键词 smart-grid communication network optimal location access point network delay genetic algorithm
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Ant Colony Algorithm for Path Planning Based on Grid Feature Point Extraction 认领 引用 被引量：13
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作者 李二超 齐款款 《Journal of Shanghai Jiaotong university(Science)》 EI 2023年第1期86-99,共14页
Aimed at the problems of a traditional ant colony algorithm,such as the path search direction and field of view,an inability to find the shortest path,a propensity toward deadlock and an unsmooth path,an ant colony al... Aimed at the problems of a traditional ant colony algorithm,such as the path search direction and field of view,an inability to find the shortest path,a propensity toward deadlock and an unsmooth path,an ant colony algorithm for use in a new environment is proposed.First,the feature points of an obstacle are extracted to preprocess the grid map environment,which can avoid entering a trap and solve the deadlock problem.Second,these feature points are used as pathfinding access nodes to reduce the node access,with more moving directions to be selected,and the locations of the feature points to be selected determine the range of the pathfinding field of view.Then,based on the feature points,an unequal distribution of pheromones and a two-way parallel path search are used to improve the construction efficiency of the solution,an improved heuristic function is used to enhance the guiding role of the path search,and the pheromone volatilization coefficient is dynamically adjusted to avoid a premature convergence of the algorithm.Third,a Bezier curve is used to smooth the shortest path obtained.Finally,using grid maps with a different complexity and different scales,a simulation comparing the results of the proposed algorithm with those of traditional and other improved ant colony algorithms verifies its feasibility and superiority. 展开更多
关键词 ant colony algorithm mobile robot path planning feature points Bezier curve grid map
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Assessing Criteria Weights by the Symmetry Point of Criterion (Novel SPC Method)–Application in the Efficiency Evaluation of the Mineral Deposit Multi-Criteria Partitioning Algorithm 认领 引用 被引量：2
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作者 Zoran Gligoric Milos Gligoric +2 位作者 Igor Miljanovic Suzana Lutovac Aleksandar Milutinovic 《Computer Modeling in Engineering & Sciences》 SCIE EI 2023年第7期955-979,共25页
Information about the relative importance of each criterion or theweights of criteria can have a significant influence on the ultimate rank of alternatives.Accordingly,assessing the weights of criteria is a very impor... Information about the relative importance of each criterion or theweights of criteria can have a significant influence on the ultimate rank of alternatives.Accordingly,assessing the weights of criteria is a very important task in solving multi-criteria decision-making problems.Three methods are commonly used for assessing the weights of criteria:objective,subjective,and integrated methods.In this study,an objective approach is proposed to assess the weights of criteria,called SPCmethod(Symmetry Point of Criterion).This point enriches the criterion so that it is balanced and easy to implement in the process of the evaluation of its influence on decision-making.The SPC methodology is systematically presented and supported by detailed calculations related to an artificial example.To validate the developed method,we used our numerical example and calculated the weights of criteria by CRITIC,Entropy,Standard Deviation and MEREC methods.Comparative analysis between these methods and the SPC method reveals that the developedmethod is a very reliable objective way to determine the weights of criteria.Additionally,in this study,we proposed the application of SPCmethod to evaluate the efficiency of themulti-criteria partitioning algorithm.The main idea of the evaluation is based on the following fact:the greater the uniformity of the weights of criteria,the higher the efficiency of the partitioning algorithm.The research demonstrates that the SPC method can be applied to solving different multi-criteria problems. 展开更多
关键词 Multi-criteria decision-making weights of criteria symmetry point of criterion mineral deposit partitioning algorithm performance evaluation
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Multi-Objective Optimization Algorithm for Grouping Decision Variables Based on Extreme Point Pareto Frontier 认领 引用 被引量：1
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作者 JunWang Linxi Zhang +4 位作者 Hao Zhang Funan Peng Mohammed A.El-Meligy Mohamed Sharaf Qiang Fu 《Computers, Materials & Continua》 SCIE EI 2024年第4期1281-1299,共19页
The existing algorithms for solving multi-objective optimization problems fall into three main categories:Decomposition-based,dominance-based,and indicator-based.Traditional multi-objective optimization problemsmainly... The existing algorithms for solving multi-objective optimization problems fall into three main categories:Decomposition-based,dominance-based,and indicator-based.Traditional multi-objective optimization problemsmainly focus on objectives,treating decision variables as a total variable to solve the problem without consideringthe critical role of decision variables in objective optimization.As seen,a variety of decision variable groupingalgorithms have been proposed.However,these algorithms are relatively broad for the changes of most decisionvariables in the evolution process and are time-consuming in the process of finding the Pareto frontier.To solvethese problems,a multi-objective optimization algorithm for grouping decision variables based on extreme pointPareto frontier(MOEA-DV/EPF)is proposed.This algorithm adopts a preprocessing rule to solve the Paretooptimal solution set of extreme points generated by simultaneous evolution in various target directions,obtainsthe basic Pareto front surface to determine the convergence effect,and analyzes the convergence and distributioneffects of decision variables.In the later stages of algorithm optimization,different mutation strategies are adoptedaccording to the nature of the decision variables to speed up the rate of evolution to obtain excellent individuals,thusenhancing the performance of the algorithm.Evaluation validation of the test functions shows that this algorithmcan solve the multi-objective optimization problem more efficiently. 展开更多
关键词 Multi-objective evolutionary optimization algorithm decision variables grouping extreme point pareto frontier
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Convergence analysis of the corrected Uzawa algorithm for symmetric saddle point problems 认领 引用 被引量：2
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作者 LU Jun-feng 《Applied Mathematics(A Journal of Chinese Universities)》 SCIE CSCD 2014年第1期29-35,共7页
For the large sparse saddle point problems, Pan and Li recently proposed in [H. K. Pan, W. Li, Math. Numer. Sinica, 2009, 31（3）： 231-242] a corrected Uzawa algorithm based on a nonlinear Uzawa algorithm with two no... For the large sparse saddle point problems, Pan and Li recently proposed in [H. K. Pan, W. Li, Math. Numer. Sinica, 2009, 31（3）： 231-242] a corrected Uzawa algorithm based on a nonlinear Uzawa algorithm with two nonlinear approximate inverses, and gave the detailed convergence analysis. In this paper, we focus on the convergence analysis of this corrected Uzawa algorithm, some inaccuracies in [H. K. Pan, W. Li, Math. Numer. Sinica, 2009, 31（3）： 231-242] are pointed out, and a corrected convergence theorem is presented. A special case of this modified Uzawa algorithm is also discussed. 展开更多
关键词 Saddle point problem Uzawa algorithm convergence analysis
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PROXIMAL POINT ALGORITHM WITH ERRORS FOR GENERALIZED STRONGLY NONLINEARQUASIVARIATIONAL INCLUSIONS 认领 引用 被引量：1
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作者 丁协平 《Applied Mathematics and Mechanics(English Edition)》 SCIE EI 1998年第7期637-643,共7页
In this paper, a class of generalized strongly nonlinear quasivariational inclusions are studied. By using the properties of the resolvent operator associated with a maximal monotone; mapping in Hilbert space, an exis... In this paper, a class of generalized strongly nonlinear quasivariational inclusions are studied. By using the properties of the resolvent operator associated with a maximal monotone; mapping in Hilbert space, an existence theorem of solutions for generalized strongly nonlinear quasivariational inclusion is established and a new proximal point algorithm with errors is suggested for finding approximate solutions which strongly converge to the exact solution of the generalized strongly, nonlinear quasivariational inclusion. As special cases, some known results in this field are also discussed. 展开更多
关键词 generalized strongly nonlinear quasivariational inclusion proximal point algorithm with errors
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AN INFEASIBLE-INTERIOR-POINT PREDICTOR-CORRECTOR ALGORITHM FOR THE SECOND-ORDER CONE PROGRAM 认领 引用 被引量：12
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作者 迟晓妮 刘三阳 《Acta Mathematica Scientia》 SCIE 2008年第3期551-559,共9页
A globally convergent infeasible-interior-point predictor-corrector algorithm is presented for the second-order cone programming （SOCP） by using the Alizadeh- Haeberly-Overton （AHO） search direction. This algorith... A globally convergent infeasible-interior-point predictor-corrector algorithm is presented for the second-order cone programming （SOCP） by using the Alizadeh- Haeberly-Overton （AHO） search direction. This algorithm does not require the feasibility of the initial points and iteration points. Under suitable assumptions, it is shown that the algorithm can find an -approximate solution of an SOCP in at most O（√n ln（ε0/ε）） iterations. The iteration-complexity bound of our algorithm is almost the same as the best known bound of feasible interior point algorithms for the SOCP. 展开更多
关键词 Second-order cone programming, infeasible-interior-point algorithm, predictor-corrector algorithm global convergence
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SL-COA:Hybrid Efficient and Enhanced Coati Optimization Algorithm for Structural Reliability Analysis 认领 引用 被引量：1
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作者 Yunhan Ling Huajun Peng +4 位作者 Yiqing Shi Chao Xu Jingzhen Yan Jingjing Wang Hui Ma 《Computer Modeling in Engineering & Sciences》 SCIE EI 2025年第4期767-808,共42页
Thetraditional first-order reliability method(FORM)often encounters challengeswith non-convergence of results or excessive calculation when analyzing complex engineering problems.To improve the global convergence spee... Thetraditional first-order reliability method(FORM)often encounters challengeswith non-convergence of results or excessive calculation when analyzing complex engineering problems.To improve the global convergence speed of structural reliability analysis,an improved coati optimization algorithm(COA)is proposed in this paper.In this study,the social learning strategy is used to improve the coati optimization algorithm(SL-COA),which improves the convergence speed and robustness of the newheuristic optimization algorithm.Then,the SL-COAis comparedwith the latest heuristic optimization algorithms such as the original COA,whale optimization algorithm(WOA),and osprey optimization algorithm(OOA)in the CEC2005 and CEC2017 test function sets and two engineering optimization design examples.The optimization results show that the proposed SL-COA algorithm has a high competitiveness.Secondly,this study introduces the SL-COA algorithm into the MPP(Most Probable Point)search process based on FORM and constructs a new reliability analysis method.Finally,the proposed reliability analysis method is verified by four mathematical examples and two engineering examples.The results show that the proposed SL-COA-assisted FORM exhibits fast convergence and avoids premature convergence to local optima as demonstrated by its successful application to problems such as composite cylinder design and support bracket analysis. 展开更多
关键词 Hybrid reliability analysis single-loop interactive hybrid analysis most probability point metaheuristic algorithms coati optimization algorithm
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Comparison of two approximal proximal point algorithms for monotone variational inequalities 认领 引用 被引量：1
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作者 TAO Min 《Journal of Zhejiang University-SCIENCE A》 SCIE EI CAS 2007年第6期969-977,共9页
Proximal point algorithms （PPA） are attractive methods for solving monotone variational inequalities （MVI）. Since solving the sub-problem exactly in each iteration is costly or sometimes impossible, various approx... Proximal point algorithms （PPA） are attractive methods for solving monotone variational inequalities （MVI）. Since solving the sub-problem exactly in each iteration is costly or sometimes impossible, various approximate versions ofPPA （APPA） are developed for practical applications. In this paper, we compare two APPA methods, both of which can be viewed as prediction-correction methods. The only difference is that they use different search directions in the correction-step. By extending the general forward-backward splitting methods, we obtain Algorithm Ⅰ; in the same way, Algorithm Ⅱ is proposed by spreading the general extra-gradient methods. Our analysis explains theoretically why Algorithm Ⅱ usually outperforms Algorithm Ⅰ. For computation practice, we consider a class of MVI with a special structure, and choose the extending Algorithm Ⅱ to implement, which is inspired by the idea of Gauss-Seidel iteration method making full use of information about the latest iteration. And in particular, self-adaptive techniques are adopted to adjust relevant parameters for faster convergence. Finally, some numerical experiments are reported on the separated MVI. Numerical results showed that the extending Algorithm II is feasible and easy to implement with relatively low computation load. 展开更多
关键词 Projection and contraction methods Proximal point algorithm （PPA） Approximate PPA （APPA） Monotone variational inequality （MVI） Prediction and correction
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KNOT POINT PLANNING FOR CARTESIAN TRAJECTORY GENERATION BASED ON INHERITANCE BISECTION ALGORITHM 认领 引用
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作者 YanBo YanGuozheng 《Chinese Journal of Mechanical Engineering》 EI CAS 2005年第2期241-245,共5页
The computation algorithm of knot point planning for Cartesian trajectorygeneration of manipulator is investigated, A novel inheritance bisection algorithm (IBA) based onconventional bisection algorithm (B A) is propo... The computation algorithm of knot point planning for Cartesian trajectorygeneration of manipulator is investigated, A novel inheritance bisection algorithm (IBA) based onconventional bisection algorithm (B A) is proposed. IBA has two steps. The first step is the 1 stknot point planning under lower set position accuracy; the second step is the 2nd knot pointplanning that inherits the results of the 1st planning under higher set position accuracy. Thesimulation results reveal that the number of inverse kinematical calculation (IKC) caused by IBA isdecreased compared with BA. IBA is more efficient to plan knot points. 展开更多
关键词 Trajectory planning Inheritance bisection algorithm Knot point planning
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Optimization of volume to point conduction problem based on a novel thermal conductivity discretization algorithm 认领 引用
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作者 杜文静 王沛丽 +1 位作者 宋立鹏 程林 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2015年第7期1161-1168,共8页
A conduction heat transfer process is enhanced by filling prescribed quantity and optimized-shaped high thermal conductivity materials to the substrate. Numerical simulations and analyses are performed on a volume to ... A conduction heat transfer process is enhanced by filling prescribed quantity and optimized-shaped high thermal conductivity materials to the substrate. Numerical simulations and analyses are performed on a volume to point conduction problem based on the principle of minimum entropy generation. In the optimization, the arrangement of high thermal conductivity materials is variable, the quantity of high thermal-conductivity material is constrained, and the objective is to obtain the maximum heat conduction rate as the entropy is the minimum.A novel algorithm of thermal conductivity discretization is proposed based on large quantity of calculations.Compared with other algorithms in literature, the average temperature in the substrate by the new algorithm is lower, while the highest temperature in the substrate is in a reasonable range. Thus the new algorithm is feasible. The optimization of volume to point heat conduction is carried out in a rectangular model with radiation boundary condition and constant surface temperature boundary condition. The results demonstrate that the algorithm of thermal conductivity discretization is applicable for volume to point heat conduction problems. 展开更多
关键词 Volume to point conduction Principle of minimum entropy generation Algorithm of thermal conductivity discretization Optimization
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