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基于MSET-MOEA/D航空数据总线异常检测 认领 引用
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作者 闫洁 王晓前 +1 位作者 刘文琪 葛红娟 《航空计算技术》 2026年第1期53-58,共6页
针对机载网络入侵检测系统样本具有不平衡性的问题,提出多元状态估计技术和基于分解的多目标进化算法(MSET-MOEA/D)相结合的方法,实现异常样本极少的航空数据总线异常检测。研究基于数据总线观测样本和估计样本偏差的初始预警阈值MSET... 针对机载网络入侵检测系统样本具有不平衡性的问题,提出多元状态估计技术和基于分解的多目标进化算法(MSET-MOEA/D)相结合的方法,实现异常样本极少的航空数据总线异常检测。研究基于数据总线观测样本和估计样本偏差的初始预警阈值MSET评估算法,提出一种综合考虑误报数和漏报数的阈值设置方法。该方法以裕量为自变量,以误报数和漏报数为目标,将异常检测问题转变为一个多目标优化问题。进一步提出基于MOEA/D的可变目标权重的Pareto解集评价方法,获得最高满意度对应的折中解。机载网络数据集以GJB289航空总线数据集开展算法的验证和比较研究。实验结果表明,所提算法不仅适用于可变的多目标权重要求,且具有漏报数或误报数更低、检测效率高的优势,实用价值更高。 展开更多
关键词 航空数据总线 异常检测 不平衡样本 多元状态估计技术 MSET MOEA/D
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基于MOEA/D和NSGA-Ⅱ算法的燃煤锅炉多目标燃烧优化 认领 引用
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作者 张浩杰 余其乐 +5 位作者 游春发 周攀 周丽娜 熊远南 邓永强 张员根 《广西电力》 2026年第1期25-32,共8页
为实现某燃煤电厂锅炉燃烧多目标优化,采用径向基函数神经网络对锅炉NOx生成浓度和锅炉热效率进行建模,预测模型显示NOx生成浓度最大预测误差6.03%、平均误差2.97%,锅炉热效率最大预测误差0.13%、平均误差0.032%。以锅炉NOx生成浓度和... 为实现某燃煤电厂锅炉燃烧多目标优化,采用径向基函数神经网络对锅炉NOx生成浓度和锅炉热效率进行建模,预测模型显示NOx生成浓度最大预测误差6.03%、平均误差2.97%,锅炉热效率最大预测误差0.13%、平均误差0.032%。以锅炉NOx生成浓度和热效率预测结果作为多目标优化算法的目标函数,分别采用基于分解的多目标进化算法(multiobjective evolutionary algorithm based on decomposition,MOEA/D)和第二代非支配排序遗传算法(non-dominated sorting genetic algorithm Ⅱ,NSGA-Ⅱ)对燃煤锅炉进行多目标燃烧优化。经过NSGA-Ⅱ优化后,锅炉NOx生成浓度为85.23~136.15 mg/m3,较历史运行最低值降低35.7%;锅炉热效率为94.6%~95.2%,较历史运行最高值提升0.86个百分点。与MOEA/D相比,NSGA-Ⅱ所得Pareto前沿具有更好的收敛性、分布性和运行速度,可为电厂提供兼具经济性与环保性的运行方案。 展开更多
关键词 燃煤锅炉 超超临界锅炉 燃烧优化 径向基函数神经网络 MOEA/D算法 NSGA-Ⅱ算法
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超高强度A柱加强板热冲压质量自适应MOEA/D优化 认领 引用 被引量：1
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作者 裴宝浩 肖振 +1 位作者 周娟 于蓬 《机械设计与制造》 北大核心 2025年第9期255-259,265,共5页
为了提高超高强度A柱加强板热冲压成形质量,提出了基于自适应MOEA/D算法的冲压参数多目标优化方法。使用数值模拟法分析了超高强度A柱加强板热冲压质量问题,并针对最大减薄率和最大增厚率建立了多目标优化模型。在仿真数据基础上,使用Kr... 为了提高超高强度A柱加强板热冲压成形质量,提出了基于自适应MOEA/D算法的冲压参数多目标优化方法。使用数值模拟法分析了超高强度A柱加强板热冲压质量问题,并针对最大减薄率和最大增厚率建立了多目标优化模型。在仿真数据基础上,使用Kriging模型拟合了质量参数与工艺参数间模型。将优化变量编码为基因,从而将冲压优化问题转化为算法寻优问题。为了提高MOEA/D算法的优化能力,在算法中引入了自适应差异性惩罚方案,进而提出了基于自适应MOEA/D算法的优化方法。经生产优化,优化后产品的金相组织实现了预期变化,最大减薄率均值由17.1%减小为14.5%,最大增厚率均值由18.1%减小为15.7%,实验结果证明了自适应MOEA/D优化算法的优越性。 展开更多
关键词 超高强度 A柱加强板 冲压优化 MOEA/D算法 自适应差异性惩罚方案
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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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3D numerical manifold method for crack propagation in rock materials using a local tracking algorithm 认领 引用 被引量：1
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作者 Boyi Su Tao Xu +3 位作者 Genhua Shi Michael J.Heap Xianyang Yu Guanglei Zhou 《Journal of Rock Mechanics and Geotechnical Engineering》 SCIE CSCD 2025年第6期3449-3463,共15页
The modeling of crack growth in three-dimensional(3D)space poses significant challenges in rock mechanics due to the complex numerical computation involved in simulating crack propagation and interaction in rock mater... The modeling of crack growth in three-dimensional(3D)space poses significant challenges in rock mechanics due to the complex numerical computation involved in simulating crack propagation and interaction in rock materials.In this study,we present a novel approach that introduces a 3D numerical manifold method(3D-NMM)with a geometric kernel to enhance computational efficiency.Specifically,the maximum tensile stress criterion is adopted as a crack growth criterion to achieve strong discontinuous crack growth,and a local crack tracking algorithm and an angle correction technique are incorporated to address minor limitations of the algorithm in a 3D model.The implementation of the program is carried out in Python,using object-oriented programming in two independent modules:a calculation module and a crack module.Furthermore,we propose feasible improvements to enhance the performance of the algorithm.Finally,we demonstrate the feasibility and effectiveness of the enhanced algorithm in the 3D-NMM using four numerical examples.This study establishes the potential of the 3DNMM,combined with the local tracking algorithm,for accurately modeling 3D crack propagation in brittle rock materials. 展开更多
关键词 3D numerical manifold method(3D NMM) Crack propagation Local tracking algorithm Brittle materials
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A novel heuristic pathfinding algorithm for 3D security modeling and vulnerability assessment 认领 引用 被引量：1
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作者 Jun Yang Yue-Ming Hong +2 位作者 Yu-Ming Lv Hao-Ming Ma Wen-Lin Wang 《Nuclear Science and Techniques》 SCIE EI CAS CSCD 2025年第5期152-166,共15页
Vulnerability assessment is a systematic process to identify security gaps in the design and evaluation of physical protection systems.Adversarial path planning is a widely used method for identifying potential vulner... Vulnerability assessment is a systematic process to identify security gaps in the design and evaluation of physical protection systems.Adversarial path planning is a widely used method for identifying potential vulnerabilities and threats to the security and resilience of critical infrastructures.However,achieving efficient path optimization in complex large-scale three-dimensional(3D)scenes remains a significant challenge for vulnerability assessment.This paper introduces a novel A*-algorithmic framework for 3D security modeling and vulnerability assessment.Within this framework,the 3D facility models were first developed in 3ds Max and then incorporated into Unity for A*heuristic pathfinding.The A*-heuristic pathfinding algorithm was implemented with a geometric probability model to refine the detection and distance fields and achieve a rational approximation of the cost to reach the goal.An admissible heuristic is ensured by incorporating the minimum probability of detection(PDmin)and diagonal distance to estimate the heuristic function.The 3D A*heuristic search was demonstrated using a hypothetical laboratory facility,where a comparison was also carried out between the A*and Dijkstra algorithms for optimal path identification.Comparative results indicate that the proposed A*-heuristic algorithm effectively identifies the most vulnerable adversarial pathfinding with high efficiency.Finally,the paper discusses hidden phenomena and open issues in efficient 3D pathfinding for security applications. 展开更多
关键词 Physical protection system 3D modeling and simulation Vulnerability assessment A*Heuristic Pathfinding Dijkstra algorithm
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基于权重调节MOEA/D的泵组能效-健康度优化研究 认领 引用 被引量：1
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作者 胡田力 陈迪 +1 位作者 梁毅 张靖宇 《自动化与仪表》 2025年第6期35-39,共5页
该文针对当前泵组控制策略无法在整个生命周期中综合工况-能效-健康度自适应地调整的问题,提出了一种多目标泵组能效-健康度优化控制模型,其3个目标函数权重系数可独立调节。采用距离偏差法确定目标函数,使用多目标粒子群算法计算工况... 该文针对当前泵组控制策略无法在整个生命周期中综合工况-能效-健康度自适应地调整的问题,提出了一种多目标泵组能效-健康度优化控制模型,其3个目标函数权重系数可独立调节。采用距离偏差法确定目标函数,使用多目标粒子群算法计算工况最稳、能耗最低和系统健康度最高的帕累托前沿最优解。对不同健康度下现场实验数据分析表明,权重调整MOEA/D模型具有求解速度快、在变权重下解集分布均匀以及帕累托解集覆盖率高的优点,从而使泵组控制策略实现工况控制目标的同时,使用寿命更长。 展开更多
关键词 MOEA/D 权重调节 能效-健康度 水泵特性曲线优化
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基于MOEA/D的高温热管参数分析及多目标优化 认领 引用 被引量：1
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作者 邢佳慧 倪浪 +2 位作者 向立平 李星佑 高帆 《节能技术》 CAS 2025年第1期92-96,F0003,共5页
为了提升高温热管工作性能,改进了传统热阻网络模型,利用MOEA/D算法优化蒸发段长度、壁厚和吸液芯厚度,以实现总热阻、传热极限和吸液芯质量流量最优,得到Pareto最优解。数值模拟结果表明:改进后的热阻网络模型与多组实验值对比总热阻... 为了提升高温热管工作性能,改进了传统热阻网络模型,利用MOEA/D算法优化蒸发段长度、壁厚和吸液芯厚度,以实现总热阻、传热极限和吸液芯质量流量最优,得到Pareto最优解。数值模拟结果表明:改进后的热阻网络模型与多组实验值对比总热阻误差均低于7%;总热阻受吸液芯厚度影响最为明显,吸液芯厚度越大总热阻越大;吸液芯质量流量与吸液芯厚度及壁厚成正比;传热极限与吸液芯厚度成反比;在750~850 K内,总热阻最佳可达0.0266 K/W,同实验值相比降低31%。本研究能提供更优的设计参数以提升热管工作性能。 展开更多
关键词 高温热管 热阻网络 参数优化 基于分解的多目标算法 Pareto最优解集
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Advanced 3D Wind Farm Layout Optimization Framework via Power-Law Perturbation-Based Genetic Algorithm 认领 引用
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作者 Jiaru Yang Yaotong Song +3 位作者 Jun Tang Weiping Ding Zhenyu Lei Shangce Gao 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2025年第11期2314-2328,共15页
The modeling and optimization of wind farm layouts can effectively reduce the wake effect between turbine units,thereby enhancing the expected output power and avoiding negative influence.Traditional wind farm optimiz... The modeling and optimization of wind farm layouts can effectively reduce the wake effect between turbine units,thereby enhancing the expected output power and avoiding negative influence.Traditional wind farm optimization often uses idealized wake models,neglecting the influence of wind shear at different elevations,which leads to a lack of precision in estimating wake effects and fails to meet the accuracy and reliability requirements of practical engineering.To address this,we have constructed a three-dimensional 3D wind farm optimization model that incorporates elevation,utilizing a 3D wake model to better reflect real-world conditions.We aim to assess the optimization state of the algorithm and provide strong incentives at the right moments to ensure continuous evolution of the population.To this end,we propose an evolutionary adaptation degreeguided genetic algorithm based on power-law perturbation(PPGA)to adapt multidimensional conditions.We select the offshore wind power project in Nantong,Jiangsu,China,as a study example and compare PPGA with other well-performing algorithms under this practical project.Based on the actual wind condition data,the experimental results demonstrate that PPGA can effectively tackle this complex problem and achieve the best power efficiency. 展开更多
关键词 3D wake model China’s southeastern coast metaheuristic offshore wind farm power-law perturbation-based genetic algorithm(PPGA)
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3D finite-difference numerical simulation of the gravitational field using a preconditioned GMRES iterative solver 认领 引用
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作者 TONG Xiao-zhong XIE Wei +3 位作者 MA Hui-ying WEN Xin-yue ZHU Wen-di ZHANG Chen 《Journal of Central South University》 SCIE EI CAS CSCD 2026年第2期847-860,共14页
With the evolution of geophysical surveys from traditional two-dimensional(2 D)to three-dimensional(3 D)models,the resulting large data volumes pose significant challenges to inversion,particularly when resolving larg... With the evolution of geophysical surveys from traditional two-dimensional(2 D)to three-dimensional(3 D)models,the resulting large data volumes pose significant challenges to inversion,particularly when resolving large-scale 3 D structures.A direct solver for solving an ill-conditioned linear system resulting from the finite-difference approximation of a boundary value problem requires more memory and time than iterative solvers.To overcome this limitation,an efficient iterative solver for 3 D finite-difference approach is introduced to calculate the 3 D gravitational potential and the associated gravitational field.Firstly,the boundary value problem associated with 3 D gravitational potential is discretized using central finite-difference technique based on right rectangular prismatic grids.The resulting large unsymmetric sparse systems are then solved using the generalized minimal residual algorithm(GMRES)iterative solver in combination with incomplete LU factorization.Secondly,to obtain high-accuracy partial derivatives of gravitational potential,a high-degree Lagrange interpolation scheme is employed.Finally,three density models are applied to test the accuracy,reliability,and flexibility of our 3 D finite-difference algorithm.All computational results demonstrate that our method provides an accurate approximation of the gravitational field and is applicable to 3 D forward modeling. 展开更多
关键词 3 D gravitational potential boundary value problem numerical simulation finite-difference algorithm GMRES iterative solver
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具有危险源环境下机器人路径的MOEA/D多目标优化 认领 引用 被引量：1
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作者 杨惠烽 曹建芳 杨玉丽 《机械设计与制造》 北大核心 2025年第12期333-338,共6页
为了减小机器人在具有不确定危险源环境下的路径长度并提高路径安全度,提出了基于自适应最优匹配MOEA/D算法的多目标优化方法。使用直线簇建立了环境模型,将二维平面路径优化问题降为一维优化问题。以减小路径长度、提高路径安全性为目... 为了减小机器人在具有不确定危险源环境下的路径长度并提高路径安全度,提出了基于自适应最优匹配MOEA/D算法的多目标优化方法。使用直线簇建立了环境模型,将二维平面路径优化问题降为一维优化问题。以减小路径长度、提高路径安全性为目标建立了多优化目标函数。在MOEA/D算法中引入了最优匹配策略和自适应邻域策略,从而提出了自适应最优匹配MOEA/D算法,并将其应用到机器人路径规划中。经仿真测试,改进MOEA/D算法的Pareto解质量高于标准MOEA/D算法和NSGA-Ⅲ算法。在具有危险源的简单和复杂环境中,改进MOEA/D算法规划的路径长度和安全性均好于文献[12]分解MOEA/D算法。实验结果验证了自适应最优匹配MOEA/D算法在具有危险源环境中路径规划的有效性和优越性。 展开更多
关键词 不确定危险源 机器人路径 多目标优化 MOEA/D算法 自适应邻域
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Path Planning for Substation UAV Inspection Based on 3D Point Cloud Mapping 认领 引用
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作者 Yanping Chen Zhengxin Zhan +3 位作者 Xiaohui Yan Le Zou Yucheng Zhong Hailei Wang 《Computers, Materials & Continua》 SCIE EI 2026年第5期2138-2159,共22页
With the increasing complexity of substation inspection tasks,achieving efficient and safe path planning for Unmanned Aerial Vehicles in densely populated and structurally complex three-dimensional(3D)environments rem... With the increasing complexity of substation inspection tasks,achieving efficient and safe path planning for Unmanned Aerial Vehicles in densely populated and structurally complex three-dimensional(3D)environments remains a critical challenge.To address this problem,this paper proposes an improved path planning algorithm—Random Geometric Graph(RGG)-guided Rapidly-exploring Random Tree(R-RRT)—based on the classical Rapidly-exploring Random Tree(RRT)framework.First,a refined 3D occupancy grid map is constructed from Light Detection and Ranging point cloud data through ground filtering,noise removal,coordinate transformation,and obstacle inflation using spherical structuring elements.During the planning stage,a dynamic goal-biasing strategy is introduced to adaptively adjust the sampling direction,the sampling distribution is optimized using a pre-generated RGG,and collision detection is accelerated via a K-Dimensional Tree structure.After initial trajectory generation,redundant nodes are eliminated via greedy pruning,and a curvature-minimizing gradient-based optimizationmethod is applied to smooth the trajectory.Experimental results conducted in a simulated substation environment demonstrate that,compared with mainstream path planning algorithms,the proposed R-RRT achieves superior performance in terms of path length,planning time,and trajectory smoothness.Comprehensive analysis shows that the proposed method significantly enhances trajectory quality,planning efficiency,and operational safety,validating its applicability and advantages for high-precision 3D path planning in complex substation inspection scenarios. 展开更多
关键词 R-RRT algorithm unmanned aerial vehicles path planning random geometric graph 3D occupancy grid map substation inspection
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基于新型贪心-D*算法的无人机全覆盖路径规划 认领 引用
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作者 周映江 谢明慧 +2 位作者 蒋国平 徐丰羽 高辉 《南京邮电大学学报（自然科学版）》 北大核心 2026年第1期111-123,共13页
针对动态未知环境中全覆盖路径规划面临的路径冗余率高和环境适应性差等难题,提出一种基于新型贪心-D*算法(Novel Greedy-D*Algorithm,NG-D*)的无人机全覆盖路径规划。首先,构建动态增量式环境建模系统,实现障碍物分布实时更... 针对动态未知环境中全覆盖路径规划面临的路径冗余率高和环境适应性差等难题,提出一种基于新型贪心-D*算法(Novel Greedy-D*Algorithm,NG-D*)的无人机全覆盖路径规划。首先,构建动态增量式环境建模系统,实现障碍物分布实时更新与矩阵化栅格状态精准映射,增强系统环境感知能力。其次,设计最小值优先三元组贪心决策函数,通过评估曼哈顿距离、横向优先级与纵向优先级,生成结构化有序覆盖路径。最后,引入关键节点导向D*逃离算法,在检测到局部死区时高效规划平滑脱离路径。实验结果表明,相较于传统方法,NG-D*算法在保持覆盖完整性的前提下,将路径冗余率降低至3.0%以下。 展开更多
关键词 D*算法 贪心策略 全覆盖路径规划 未知环境 无人机
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Non-Neural 3D Nasal Reconstruction:A Sparse Landmark Algorithmic Approach for Medical Applications 认领 引用 被引量：1
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作者 Nguyen Khac Toan Ho Nguyen Anh Tuan Nguyen Truong Thinh 《Computer Modeling in Engineering & Sciences》 SCIE EI 2025年第5期1273-1295,共23页
This paper presents a novel method for reconstructing a highly accurate 3D nose model of the human from 2D images and pre-marked landmarks based on algorithmic methods.The study focuses on the reconstruction of a 3D n... This paper presents a novel method for reconstructing a highly accurate 3D nose model of the human from 2D images and pre-marked landmarks based on algorithmic methods.The study focuses on the reconstruction of a 3D nose model tailored for applications in healthcare and cosmetic surgery.The approach leverages advanced image processing techniques,3D Morphable Models(3DMM),and deformation techniques to overcome the limita-tions of deep learning models,particularly addressing the interpretability issues commonly encountered in medical applications.The proposed method estimates the 3D coordinates of landmark points using a 3D structure estimation algorithm.Sub-landmarks are extracted through image processing techniques and interpolation.The initial surface is generated using a 3DMM,though its accuracy remains limited.To enhance precision,deformation techniques are applied,utilizing the coordinates of 76 identified landmarks and sub-landmarks.The resulting 3D nose model is constructed based on algorithmic methods and pre-marked landmarks.Evaluation of the 3D model is conducted by comparing landmark distances and shape similarity with expert-determined ground truth on 30 Vietnamese volunteers aged 18 to 47,all of whom were either preparing for or required nasal surgery.Experimental results demonstrate a strong agreement between the reconstructed 3D model and the ground truth.The method achieved a mean landmark distance error of 0.631 mm and a shape error of 1.738 mm,demonstrating its potential for medical applications. 展开更多
关键词 Nose reconstruction 3D reconstruction medical applications algorithmic reconstruction enhanced 3D model
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Flexible Monolithic 3D-Integrated Self-Powered Tactile Sensing Array Based on Holey MXene Paste 认领 引用 被引量：4
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作者 Mengjie Wang Chen Chen +9 位作者 Yuhang Zhang Yanan Ma Li Xu Dan‑Dan Wu Bowen Gao Aoyun Song Li Wen Yongfa Cheng Siliang Wang Yang Yue 《Nano-Micro Letters》 SCIE EI CAS CSCD 2026年第2期772-785,共14页
Flexible electronics face critical challenges in achieving monolithic three-dimensional(3D)integration,including material compatibility,structural stability,and scalable fabrication methods.Inspired by the tactile sen... Flexible electronics face critical challenges in achieving monolithic three-dimensional(3D)integration,including material compatibility,structural stability,and scalable fabrication methods.Inspired by the tactile sensing mechanism of the human skin,we have developed a flexible monolithic 3D-integrated tactile sensing system based on a holey MXene paste,where each vertical one-body unit simultaneously functions as a microsupercapacitor and pressure sensor.The in-plane mesopores of MXene significantly improve ion accessibility,mitigate the self-stacking of nanosheets,and allow the holey MXene to multifunctionally act as a sensing material,an active electrode,and a conductive interconnect,thus drastically reducing the interface mismatch and enhancing the mechanical robustness.Furthermore,we fabricate a large-scale device using a blade-coating and stamping method,which demonstrates excellent mechanical flexibility,low-power consumption,rapid response,and stable long-term operation.As a proof-of-concept application,we integrate our sensing array into a smart access control system,leveraging deep learning to accurately identify users based on their unique pressing behaviors.This study provides a promising approach for designing highly integrated,intelligent,and flexible electronic systems for advanced human-computer interactions and personalized electronics. 展开更多
关键词 Holey MXene Microsupercapacitor Tactile sensor Monolithic 3D integration Deep learning algorithm
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融合VFM与D*算法的WSN动态栅栏覆盖优化 认领 引用
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作者 余修武 周颖 +1 位作者 尹文辉 叶莱 《电子科技大学学报》 EI CAS CSCD 北大核心 2026年第3期385-397,共13页
为了解决无线传感器网络(WSN)的覆盖优化问题,提出了一种基于动态参数调控和虚拟力增强的动态栅栏覆盖PSO算法(DPVF-PSO)。首先,初始化网络参数和粒子群参数,随机生成初始群体的位置和速度,并计算每个粒子的适应度值。随后,在迭代过程... 为了解决无线传感器网络(WSN)的覆盖优化问题,提出了一种基于动态参数调控和虚拟力增强的动态栅栏覆盖PSO算法(DPVF-PSO)。首先,初始化网络参数和粒子群参数,随机生成初始群体的位置和速度,并计算每个粒子的适应度值。随后,在迭代过程中动态调整PSO参数,计算节点间的虚拟力,选择目标栅栏区域,并融合D*算法寻找最短路径,更新粒子的速度和位置,同时进行适应度评估。每隔若干代进行一次局部搜索,以进一步优化全局最优解。尤其在含障碍物的检测区域内,DPVF-PSO通过虚拟力机制引导节点避开障碍物,同时利用D*算法规划最短路径,优化节点的移动轨迹,减少传输延迟和能量消耗,确保网络覆盖的有效性和通信连通性。实验结果表明,在有障碍物的环境中,DPVF-PSO的覆盖率比Chaos ABC、IIC-CS、IHPO和HHO算法分别高出3.623%、5.762%、10.643%和4.385%,适用于智能交通管理、环境监测等实际应用场景,具有显著的实用价值。 展开更多
关键词 无线传感器网络 粒子群优化 D*算法 虚拟力算法 动态参数调整 栅栏覆盖
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基于改进D* Lite与APF算法的机器人动态路径规划 认领 引用
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作者 赵卫东 倪永顺 陈昊然 《安徽工业大学学报（自然科学版）》 CAS 2026年第2期181-190,共10页
针对动态环境下机器人路径规划存在的搜索时间长、路径不平滑及避障性能不足等问题,提出一种融合D* Lite算法与人工势场法(artificial potential field,APF)的路径平滑优化算法。首先,通过优化D* Lite算法的启发函数和键值算子提... 针对动态环境下机器人路径规划存在的搜索时间长、路径不平滑及避障性能不足等问题,提出一种融合D* Lite算法与人工势场法(artificial potential field,APF)的路径平滑优化算法。首先,通过优化D* Lite算法的启发函数和键值算子提升搜索效率;进而改进APF斥力函数并引入随机虚拟障碍物,以解决机器人易陷入局部最优的问题,并通过引力-斥力协同机制实现目标趋近于动态避障。算法融合实现了动态环境下路径的快速搜索与高效避障,为进一步提升路径规划的实用性与运动流畅性,采用剪枝策略去除冗余节点以降低运算复杂度,并减少不必要转向以降低路径曲折度;在此基础上引入三次B样条曲线对路径进行平滑处理,消除尖锐拐点,生成符合运动学规律的平滑路径。仿真实验结果表明:相较于传统D* Lite算法,本文算法在简单、复杂和狭窄通道三类典型环境中,搜索时间分别减少13.3%,9.3%和11.5%,路径平滑度与避障能力显著提升,实现了高效全局规划和局部动态避障的有效结合,显著缩短了路径搜索时间,验证了算法的优越性与实用性,为动态环境下机器人高效、平滑与鲁棒的路径规划提供了有效解决方案。 展开更多
关键词 D*Lite算法 APF算法 路径规划 动态避障 启发函数 路径平滑 实时规划 智能机器人
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Hybrid Framework for Structural Analysis: Integrating Topology Optimization, Adjacent Element Temperature-Driven Pre-Stress, and Greedy Algorithms 认领 引用
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作者 Ibrahim T.Teke Ahmet H.Ertas 《Computers, Materials & Continua》 SCIE EI 2025年第7期243-264,共22页
This study presents a novel hybrid topology optimization and mold design framework that integrates process fitting,runner system optimization,and structural analysis to significantly enhance the performance of injecti... This study presents a novel hybrid topology optimization and mold design framework that integrates process fitting,runner system optimization,and structural analysis to significantly enhance the performance of injection-molded parts.At its core,the framework employs a greedy algorithm that generates runner systems based on adjacency and shortest path principles,leading to improvements in both mechanical strength and material efficiency.The design optimization is validated through a series of rigorous experimental tests,including three-point bending and torsion tests performed on key-socket frames,ensuring that the optimized designs meet practical performance requirements.A critical innovation of the framework is the development of the Adjacent Element Temperature-Driven Prestress Algorithm(AETDPA),which refines the prediction of mechanical failure and strength fitting.This algorithm has been shown to deliver mesh-independent accuracy,thereby enhancing the reliability of simulation results across various design iterations.The framework’s adaptability is further demonstrated by its ability to adjust optimization methods based on the unique geometry of each part,thus accelerating the overall design process while ensuring struc-tural integrity.In addition to its immediate applications in injection molding,the study explores the potential extension of this framework to metal additive manufacturing,opening new avenues for its use in advanced manufacturing technologies.Numerical simulations,including finite element analysis,support the experimental findings and confirm that the optimized designs provide a balanced combination of strength,durability,and efficiency.Furthermore,the integration challenges with existing injection molding practices are addressed,underscoring the framework’s scalability and industrial relevance.Overall,this hybrid topology optimization framework offers a computationally efficient and robust solution for advanced manufacturing applications,promising significant improvements in design efficiency,cost-effectiveness,and product performance.Future work will focus on further enhancing algorithm robustness and exploring additional applications across diverse manufacturing processes. 展开更多
关键词 Plastic injection molding 3D printing three-point bending tensile test adjacent element temperature-driven pre-stress algorithm D-S-ER S-D-S-ER thermal expansion greedy algorithm
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Indoor space layout research based on redirection algorithm 认领 引用
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作者 Qizhao WANG 《虚拟现实与智能硬件（中英文）》 EI CSCD 2025年第6期618-638,共21页
Background Advancements in computer science and knowledge have made the incorporation of control theory,graphics processing,and mathematical models increasingly important for urban design planning.However,challenges r... Background Advancements in computer science and knowledge have made the incorporation of control theory,graphics processing,and mathematical models increasingly important for urban design planning.However,challenges remain in aligning virtual reality(VR)environments with real-world spatial and preparation requirements,particularly in indoor urban spaces.Methods This study investigates the application of VR technology to urban design,focusing on the growth and assessment of the redirection of the space-tree sorter algorithm(STSA).It outlines various assessment indicators,organization of the VR-based system architecture,and construction of 3D urban models and databases.This research also examined methods for the interactive adjustment of indoor space layout plans within a VR environment.Results This research study involved developing and demonstrating the creation and simulation of urban indoor spaces and cityscapes in VR and implementing an experimental setup to test layout modifications and system interactivity.The results indicated enhanced alignment between the virtual and physical spatial configurations.The analysis highlights the strengths and limitations of current VR systems for urban design and identifies key areas for optimization and refinement.Conclusion High congruence between virtual simulations and real-world urban spaces is necessary for effective VR-driven urban planning.This study contributes to a clearer understanding of how 3D modeling,interactive layout design,and reproduction technology can be efficiently employed to support urban increase initiatives. 展开更多
关键词 Virtual reality(VR) Indoor space layout 3D visualization Space-Trek Sorter algorithm Redirection algorithm
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基于自适应惩罚MOEA/D的车间布局与调度优化研究 认领 引用
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作者 张雅云 《自动化应用》 2025年第9期268-271,共4页
车间布局与调度的联合优化是提高制造企业生产效率和降低成本的关键技术之一。提出了一种基于自适应惩罚MOEA/D的多目标优化方法,通过将车间布局与调度问题进行数学建模,构建多目标函数,并采用自适应惩罚因子来平衡解的多样性与收敛性... 车间布局与调度的联合优化是提高制造企业生产效率和降低成本的关键技术之一。提出了一种基于自适应惩罚MOEA/D的多目标优化方法,通过将车间布局与调度问题进行数学建模,构建多目标函数,并采用自适应惩罚因子来平衡解的多样性与收敛性。该方法有效解决了传统优化算法在处理复杂多目标问题时存在的早熟收敛和解的局部性问题。结果表明,基于自适应惩罚MOEA/D的联合优化方案在减少物流费用和缩短完工时间上表现优异,为车间布局与调度的实际应用提供了理论支持。 展开更多
关键词 联合优化 车间布局 生产调度 自适应惩罚MOEA/D
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