In this paper, we applied the rough sets to the point cluster and river network selection. In order to meet the requirements of rough sets, first, we structuralize and quantify the spatial information of objects by co...In this paper, we applied the rough sets to the point cluster and river network selection. In order to meet the requirements of rough sets, first, we structuralize and quantify the spatial information of objects by convex hull, triangulated irregular network (TIN), Voronoi diagram, etc.;second, we manually assign decisional attributes to the information table according to conditional attributes. In doing so, the spatial information and attribute information are integrated together to evaluate the importance of points and rivers by rough sets theory. Finally, we select the point cluster and the river network in a progressive manner. The experimental results show that our method is valid and effective. In comparison with previous work, our method has the advantage to adaptively consider the spatial and attribute information at the same time without any a priori knowledge.展开更多
Reduced order models(ROMs) based on the snapshots on the CFD high-fidelity simulations have been paid great attention recently due to their capability of capturing the features of the complex geometries and flow confi...Reduced order models(ROMs) based on the snapshots on the CFD high-fidelity simulations have been paid great attention recently due to their capability of capturing the features of the complex geometries and flow configurations. To improve the efficiency and precision of the ROMs, it is indispensable to add extra sampling points to the initial snapshots, since the number of sampling points to achieve an adequately accurate ROM is generally unknown in prior, but a large number of initial sampling points reduces the parsimony of the ROMs. A fuzzy-clustering-based adding-point strategy is proposed and the fuzzy clustering acts an indicator of the region in which the precision of ROMs is relatively low. The proposed method is applied to construct the ROMs for the benchmark mathematical examples and a numerical example of hypersonic aerothermodynamics prediction for a typical control surface. The proposed method can achieve a 34.5% improvement on the efficiency than the estimated mean squared error prediction algorithm and shows same-level prediction accuracy.展开更多
针对大跨径钢结构桥梁高强螺栓群松动病害人工巡检效率低、风险大及智能化检测中数据集样本不足、检测精度不高、泛化性较弱等问题,提出一种基于深度学习的钢结构桥梁高强螺栓群松动病害识别方法。首先利用基于深度学习的YOLOv10(You On...针对大跨径钢结构桥梁高强螺栓群松动病害人工巡检效率低、风险大及智能化检测中数据集样本不足、检测精度不高、泛化性较弱等问题,提出一种基于深度学习的钢结构桥梁高强螺栓群松动病害识别方法。首先利用基于深度学习的YOLOv10(You Only Look Once version 10)目标检测算法对螺栓进行目标检测;其次采用匈牙利(Kuhn-Munkres)算法对高强螺栓群基准图和待检测图进行二分匹配,同时将图片划分为单螺栓子图;然后提出一种多任务学习注意力机制的高强螺栓关键点检测算法,设计空间聚类的螺栓六角点后处理模块,融合透视变换,自上而下检测螺栓6个角点;最后对比基准图与待检测图螺栓关键点的变化,计算螺栓松动角度。采用该方法对复杂环境下的室内、室外钢桁梁节段模型及实桥钢桁梁上的高强螺栓群进行检测试验。结果表明:该方法能准确检测出螺栓是否松动,检测准确率达到了97%以上,召回率均达到了95%以上,该方法具有较好的实用价值和工程前景。展开更多
An empirical dynamic model of burn-through point（BTP）in sintering process was developed.The K-means clustering was used to feed distribution according to the cold bed permeability,which was estimated by the superfic...An empirical dynamic model of burn-through point（BTP）in sintering process was developed.The K-means clustering was used to feed distribution according to the cold bed permeability,which was estimated by the superficial gas velocity in the cold stage.For each clustering,a novel genetic programming（NGP）was proposed to construct the empirical model of the waste gas temperature and the bed pressure drop in the sintering stage.The least square method（LSM）and M-estimator were adopted in NGP to improve the ability to compute and resist disturbance.Simulation results show the superiority of the proposed method.展开更多
文摘In this paper, we applied the rough sets to the point cluster and river network selection. In order to meet the requirements of rough sets, first, we structuralize and quantify the spatial information of objects by convex hull, triangulated irregular network (TIN), Voronoi diagram, etc.;second, we manually assign decisional attributes to the information table according to conditional attributes. In doing so, the spatial information and attribute information are integrated together to evaluate the importance of points and rivers by rough sets theory. Finally, we select the point cluster and the river network in a progressive manner. The experimental results show that our method is valid and effective. In comparison with previous work, our method has the advantage to adaptively consider the spatial and attribute information at the same time without any a priori knowledge.
基金Supported by National Natural Science Foundation of China(Grant No.11372036)
文摘Reduced order models(ROMs) based on the snapshots on the CFD high-fidelity simulations have been paid great attention recently due to their capability of capturing the features of the complex geometries and flow configurations. To improve the efficiency and precision of the ROMs, it is indispensable to add extra sampling points to the initial snapshots, since the number of sampling points to achieve an adequately accurate ROM is generally unknown in prior, but a large number of initial sampling points reduces the parsimony of the ROMs. A fuzzy-clustering-based adding-point strategy is proposed and the fuzzy clustering acts an indicator of the region in which the precision of ROMs is relatively low. The proposed method is applied to construct the ROMs for the benchmark mathematical examples and a numerical example of hypersonic aerothermodynamics prediction for a typical control surface. The proposed method can achieve a 34.5% improvement on the efficiency than the estimated mean squared error prediction algorithm and shows same-level prediction accuracy.
文摘针对大跨径钢结构桥梁高强螺栓群松动病害人工巡检效率低、风险大及智能化检测中数据集样本不足、检测精度不高、泛化性较弱等问题,提出一种基于深度学习的钢结构桥梁高强螺栓群松动病害识别方法。首先利用基于深度学习的YOLOv10(You Only Look Once version 10)目标检测算法对螺栓进行目标检测;其次采用匈牙利(Kuhn-Munkres)算法对高强螺栓群基准图和待检测图进行二分匹配,同时将图片划分为单螺栓子图;然后提出一种多任务学习注意力机制的高强螺栓关键点检测算法,设计空间聚类的螺栓六角点后处理模块,融合透视变换,自上而下检测螺栓6个角点;最后对比基准图与待检测图螺栓关键点的变化,计算螺栓松动角度。采用该方法对复杂环境下的室内、室外钢桁梁节段模型及实桥钢桁梁上的高强螺栓群进行检测试验。结果表明:该方法能准确检测出螺栓是否松动,检测准确率达到了97%以上,召回率均达到了95%以上,该方法具有较好的实用价值和工程前景。
基金Sponsored by National Natural Science Foundation of China(60736021,21076179)National High-Technologies Research and Development Program of China(863 Program)(2006AA04Z184,2007AA041406)+1 种基金Key Technologies Research and Development Program of Zhejiang Province of China(2006C11066,2006C31051)Natural Science Foundation of Zhejiang Province of China(Y4080339)
文摘An empirical dynamic model of burn-through point（BTP）in sintering process was developed.The K-means clustering was used to feed distribution according to the cold bed permeability,which was estimated by the superficial gas velocity in the cold stage.For each clustering,a novel genetic programming（NGP）was proposed to construct the empirical model of the waste gas temperature and the bed pressure drop in the sintering stage.The least square method（LSM）and M-estimator were adopted in NGP to improve the ability to compute and resist disturbance.Simulation results show the superiority of the proposed method.
