The metallic softness parameterαr 0 determines the structure of the cluster and governs the rule of magic numbers. Using molecular dynamic method, the stable structures and magic numbers are determined for the cluste...The metallic softness parameterαr 0 determines the structure of the cluster and governs the rule of magic numbers. Using molecular dynamic method, the stable structures and magic numbers are determined for the clusters consisting of 13 up to 147 atoms in medium range Morse potentials, which is suitable for most of metals. As the number of atoms constituting the cluster increases, the stable structures undergo transition from face-centered (FC) to edge-centered (EC) structures. The magic number take ones of FC series before transition and take ones of EC series after that. The transition point from FC to EC structures depends on the value of softness parameter.展开更多
One of the most important problems of clustering is to define the number of classes. In fact, it is not easy to find an appropriate method to measure whether the cluster configuration is acceptable or not. In this pap...One of the most important problems of clustering is to define the number of classes. In fact, it is not easy to find an appropriate method to measure whether the cluster configuration is acceptable or not. In this paper we propose a possible and non-automatic solution considering different criteria of clustering and comparing their results. In this way robust structures of an analyzed dataset can be often caught （or established） and an optimal cluster configuration, which presents a meaningful association, may be defined. In particular, we also focus on the variables which may be used in cluster analysis. In fact, variables which contain little clustering information can cause misleading and not-robustness results. Therefore, three algorithms are employed in this study： K-means partitioning methods, Partitioning Around Medoids （PAM） and the Heuristic Identification of Noisy Variables （HINoV）. The results are compared with robust methods ones.展开更多
Refined 3D modeling of mine slopes is pivotal for precise prediction of geological hazards.Aiming at the inadequacy of existing single modeling methods in comprehensively representing the overall and localized charact...Refined 3D modeling of mine slopes is pivotal for precise prediction of geological hazards.Aiming at the inadequacy of existing single modeling methods in comprehensively representing the overall and localized characteristics of mining slopes,this study introduces a new method that fuses model data from Unmanned aerial vehicles(UAV)tilt photogrammetry and 3D laser scanning through a data alignment algorithm based on control points.First,the mini batch K-Medoids algorithm is utilized to cluster the point cloud data from ground 3D laser scanning.Then,the elbow rule is applied to determine the optimal cluster number(K0),and the feature points are extracted.Next,the nearest neighbor point algorithm is employed to match the feature points obtained from UAV tilt photogrammetry,and the internal point coordinates are adjusted through the distanceweighted average to construct a 3D model.Finally,by integrating an engineering case study,the K0 value is determined to be 8,with a matching accuracy between the two model datasets ranging from 0.0669 to 1.0373 mm.Therefore,compared with the modeling method utilizing K-medoids clustering algorithm,the new modeling method significantly enhances the computational efficiency,the accuracy of selecting the optimal number of feature points in 3D laser scanning,and the precision of the 3D model derived from UAV tilt photogrammetry.This method provides a research foundation for constructing mine slope model.展开更多
聚类分析针对不同的数据特点采用不同的相似性度量,现实世界中数据分布复杂,存在分布无规律、密度不均匀等现象,单独考虑实例属性相似性或分布结构连通性会影响聚类效果。为此,提出了一种基于属性相似性和分布结构连通性的聚类算法(A Cl...聚类分析针对不同的数据特点采用不同的相似性度量,现实世界中数据分布复杂,存在分布无规律、密度不均匀等现象,单独考虑实例属性相似性或分布结构连通性会影响聚类效果。为此,提出了一种基于属性相似性和分布结构连通性的聚类算法(A Clustering Algorithm Based on Attribute Similarity and Distributed Structure Connectivity, ASDSC)。首先,利用待聚类数据集中的所有数据实例构建完全无向图,定义了一种兼顾属性相似和分布结构连通的新颖相似性度量方式,用于计算节点相似性,并构造邻接矩阵更新边的权重;其次,借助邻接矩阵执行递增步长的随机游走,依据顶点的连通中心性来识别簇中心并给定簇编号,同时获取其他顶点的连通性;然后,利用连通性计算顶点间的依赖关系,并据此进行簇编号的传播,直至完成聚类。最后,为了验证该方法的聚类性能,在16个合成数据集和10个真实数据集上与5种先进聚类算法进行了对比实验,ASDSC算法取得了优异性能。展开更多
针对K-means算法进行大跨屋盖结构表面风荷载分区中存在的分类数k值需凭经验事先给定以及所有初始聚类中心均需随机选取带来的分类情况数过多、从中寻找最优分类结果工作量大且效率低的问题,提出基于改进K-means算法的大跨屋盖结构表面...针对K-means算法进行大跨屋盖结构表面风荷载分区中存在的分类数k值需凭经验事先给定以及所有初始聚类中心均需随机选取带来的分类情况数过多、从中寻找最优分类结果工作量大且效率低的问题,提出基于改进K-means算法的大跨屋盖结构表面风荷载分区方法。首先,建立分类数k与其相应测点风荷载的误差平方和(Sum of the Squared Errors:SSE)关系曲线,引入手肘法基本思想,实现最优分类数kst值的精准识别;其次,在首个初始聚类中心随机选取基础上,引入轮盘法基本思想,完成对剩余初始聚类中心的高效选取;然后,根据类内紧凑、类间分散的原则,通过类内紧凑性判定指标S(k)和类间分散性判定指标D(k),构造并借助SD(k)值有效性检验,得到最优的风荷载分区结果;最后,以北京奥林匹克网球中心大跨悬挑屋盖结构为例,针对风洞试验所得风荷载测试结果,采用所提方法对其表面最不利风压系数进行分区计算,并与传统K-means算法进行对比,结果表明,所提方法能够高效实现大跨屋盖结构表面风压分区计算,具有较好的工程应用价值。展开更多
Percolation theory deals with the numbers and properties of the clusters formed in the different occupation probability. In this Paper, we study the calculation method of small clusters. We calcu-lated the small clust...Percolation theory deals with the numbers and properties of the clusters formed in the different occupation probability. In this Paper, we study the calculation method of small clusters. We calcu-lated the small cluster density of 1, 2 and 3 in the percolation model with the exact method and the numerical method. The results of the two methods are very close, which can be verified by each other. We find that the cluster density of all three kinds of small clusters reaches the highest value when the occupation probability is between 0.1 and 0.2. It is very difficult to get the analytical formula for the exact method when the cluster area is relatively large (such as the area is more than 50), so we can get the density value of the cluster by numerical method. We find that the time required calculating the cluster density is proportional to the percolation area, which is indepen-dent of the cluster size and the occupation probability.展开更多
为解决传统LEACH(Low Energy Adaptive Clustering Hierarchy)协议网络节点能量消耗高、存活数量少和生存寿命短等问题,提出了一种LEACH-AD改进方案。该算法引入最优簇头比率P值、加入距离因子、剩余能量因子和密度因子等因素更新的阈...为解决传统LEACH(Low Energy Adaptive Clustering Hierarchy)协议网络节点能量消耗高、存活数量少和生存寿命短等问题,提出了一种LEACH-AD改进方案。该算法引入最优簇头比率P值、加入距离因子、剩余能量因子和密度因子等因素更新的阈值公式进行分簇以及簇间的传输。实验结果表明,改进后的LEACH-AD协议在首个死亡节点、10%死亡节点以及全部死亡节点分别比原LEACH协议延长138轮、195轮、628轮。在能量消耗方面比原LEACH协议多持续了631轮,改进后的路由协议减少了网络节点的能量消耗量,从而有效延长了无线网络与传感节点的工作时间,这对无线监测系统的研究与开发意义重大。展开更多
To the problem that it is hard to determine the clustering number and the abnormal points by using the clustering validity function, an effective clustering partition model based on the genetic algorithm is built in t...To the problem that it is hard to determine the clustering number and the abnormal points by using the clustering validity function, an effective clustering partition model based on the genetic algorithm is built in this paper. The solution to the problem is formed by the combination of the clustering partition and the encoding samples, and the fitness function is defined by the distances among and within clusters. The clustering number and the samples in each cluster are determined and the abnormal points are distinguished by implementing the triple random crossover operator and the mutation. Based on the known sample data, the results of the novel method and the clustering validity function are compared. Numerical experiments are given and the results show that the novel method is more effective.展开更多
In the past 30 years, Chinese enterprises have been a hot topic of discussion and concern among the general public in terms of economic and social status, ownership structure, business mechanism, and management level....In the past 30 years, Chinese enterprises have been a hot topic of discussion and concern among the general public in terms of economic and social status, ownership structure, business mechanism, and management level. Solving the problem of employment for the people is an important prerequisite for their peaceful living and work, as well as a prerequisite and foundation for building a harmonious society. The employment situation of private enterprises has always been of great concern to the outside world, and these two major jobs have always occupied an important position in the employment field of China that cannot be ignored. With the establishment of the market economy system, individual and private enterprises have become important components of the socialist economy, making significant contributions to economic development and social progress. The rapid development of China’s economy, on the one hand, is the embodiment of the superiority of China’s socialist market economic system, and on the other hand, it is the role of the tertiary industry and private enterprises in promoting the national economy. Since the 1990s, China’s private enterprises have become a new economic growth point for local and even national countries, and are one of the important ways to arrange employment and achieve social stability. This paper studies the employment of private enterprises and individuals from the perspective of statistics, extracts relevant data from China statistical Yearbook, uses the relevant knowledge of statistics to process the data, obtains the conclusion and puts forward relevant constructive suggestions.展开更多
The cavitation cloud of different internal structures results in different collapse pressures owing to the interaction among bubbles. The internal structure of cloud cavitation is required to accurately predict collap...The cavitation cloud of different internal structures results in different collapse pressures owing to the interaction among bubbles. The internal structure of cloud cavitation is required to accurately predict collapse pressure. A cavitation model was developed through dimensional analysis and direct numerical simulation of collapse of bubble cluster. Bubble number density was included in proposed model to characterize the internal structure of bubble cloud. Implemented on flows over a projectile, the proposed model predicts a higher collapse pressure compared with Singhal model. Results indicate that the collapse pressure of detached cavitation cloud is affected by bubble number density.展开更多
Clustering data with varying densities and complicated structures is important,while many existing clustering algorithms face difficulties for this problem. The reason is that varying densities and complicated structu...Clustering data with varying densities and complicated structures is important,while many existing clustering algorithms face difficulties for this problem. The reason is that varying densities and complicated structure make single algorithms perform badly for different parts of data. More intensive parts are assumed to have more information probably,an algorithm clustering from high density part is proposed,which begins from a tiny distance to find the highest density-connected partition and form corresponding super cores,then distance is iteratively increased by a global heuristic method to cluster parts with different densities. Mean of silhouette coefficient indicates the cluster performance. Denoising function is implemented to eliminate influence of noise and outliers. Many challenging experiments indicate that the algorithm has good performance on data with widely varying densities and extremely complex structures. It decides the optimal number of clusters automatically.Background knowledge is not needed and parameters tuning is easy. It is robust against noise and outliers.展开更多
基金Supported by the National Natural Science Foundation of China(196 740 42 198340 70 ) Science and Technology Program of Natio
文摘The metallic softness parameterαr 0 determines the structure of the cluster and governs the rule of magic numbers. Using molecular dynamic method, the stable structures and magic numbers are determined for the clusters consisting of 13 up to 147 atoms in medium range Morse potentials, which is suitable for most of metals. As the number of atoms constituting the cluster increases, the stable structures undergo transition from face-centered (FC) to edge-centered (EC) structures. The magic number take ones of FC series before transition and take ones of EC series after that. The transition point from FC to EC structures depends on the value of softness parameter.
文摘One of the most important problems of clustering is to define the number of classes. In fact, it is not easy to find an appropriate method to measure whether the cluster configuration is acceptable or not. In this paper we propose a possible and non-automatic solution considering different criteria of clustering and comparing their results. In this way robust structures of an analyzed dataset can be often caught （or established） and an optimal cluster configuration, which presents a meaningful association, may be defined. In particular, we also focus on the variables which may be used in cluster analysis. In fact, variables which contain little clustering information can cause misleading and not-robustness results. Therefore, three algorithms are employed in this study： K-means partitioning methods, Partitioning Around Medoids （PAM） and the Heuristic Identification of Noisy Variables （HINoV）. The results are compared with robust methods ones.
基金funded by National Natural Science Foundation of China(Grant Nos.42272333,42277147).
文摘Refined 3D modeling of mine slopes is pivotal for precise prediction of geological hazards.Aiming at the inadequacy of existing single modeling methods in comprehensively representing the overall and localized characteristics of mining slopes,this study introduces a new method that fuses model data from Unmanned aerial vehicles(UAV)tilt photogrammetry and 3D laser scanning through a data alignment algorithm based on control points.First,the mini batch K-Medoids algorithm is utilized to cluster the point cloud data from ground 3D laser scanning.Then,the elbow rule is applied to determine the optimal cluster number(K0),and the feature points are extracted.Next,the nearest neighbor point algorithm is employed to match the feature points obtained from UAV tilt photogrammetry,and the internal point coordinates are adjusted through the distanceweighted average to construct a 3D model.Finally,by integrating an engineering case study,the K0 value is determined to be 8,with a matching accuracy between the two model datasets ranging from 0.0669 to 1.0373 mm.Therefore,compared with the modeling method utilizing K-medoids clustering algorithm,the new modeling method significantly enhances the computational efficiency,the accuracy of selecting the optimal number of feature points in 3D laser scanning,and the precision of the 3D model derived from UAV tilt photogrammetry.This method provides a research foundation for constructing mine slope model.
文摘聚类分析针对不同的数据特点采用不同的相似性度量,现实世界中数据分布复杂,存在分布无规律、密度不均匀等现象,单独考虑实例属性相似性或分布结构连通性会影响聚类效果。为此,提出了一种基于属性相似性和分布结构连通性的聚类算法(A Clustering Algorithm Based on Attribute Similarity and Distributed Structure Connectivity, ASDSC)。首先,利用待聚类数据集中的所有数据实例构建完全无向图,定义了一种兼顾属性相似和分布结构连通的新颖相似性度量方式,用于计算节点相似性,并构造邻接矩阵更新边的权重;其次,借助邻接矩阵执行递增步长的随机游走,依据顶点的连通中心性来识别簇中心并给定簇编号,同时获取其他顶点的连通性;然后,利用连通性计算顶点间的依赖关系,并据此进行簇编号的传播,直至完成聚类。最后,为了验证该方法的聚类性能,在16个合成数据集和10个真实数据集上与5种先进聚类算法进行了对比实验,ASDSC算法取得了优异性能。
文摘针对K-means算法进行大跨屋盖结构表面风荷载分区中存在的分类数k值需凭经验事先给定以及所有初始聚类中心均需随机选取带来的分类情况数过多、从中寻找最优分类结果工作量大且效率低的问题,提出基于改进K-means算法的大跨屋盖结构表面风荷载分区方法。首先,建立分类数k与其相应测点风荷载的误差平方和(Sum of the Squared Errors:SSE)关系曲线,引入手肘法基本思想,实现最优分类数kst值的精准识别;其次,在首个初始聚类中心随机选取基础上,引入轮盘法基本思想,完成对剩余初始聚类中心的高效选取;然后,根据类内紧凑、类间分散的原则,通过类内紧凑性判定指标S(k)和类间分散性判定指标D(k),构造并借助SD(k)值有效性检验,得到最优的风荷载分区结果;最后,以北京奥林匹克网球中心大跨悬挑屋盖结构为例,针对风洞试验所得风荷载测试结果,采用所提方法对其表面最不利风压系数进行分区计算,并与传统K-means算法进行对比,结果表明,所提方法能够高效实现大跨屋盖结构表面风压分区计算,具有较好的工程应用价值。
文摘Percolation theory deals with the numbers and properties of the clusters formed in the different occupation probability. In this Paper, we study the calculation method of small clusters. We calcu-lated the small cluster density of 1, 2 and 3 in the percolation model with the exact method and the numerical method. The results of the two methods are very close, which can be verified by each other. We find that the cluster density of all three kinds of small clusters reaches the highest value when the occupation probability is between 0.1 and 0.2. It is very difficult to get the analytical formula for the exact method when the cluster area is relatively large (such as the area is more than 50), so we can get the density value of the cluster by numerical method. We find that the time required calculating the cluster density is proportional to the percolation area, which is indepen-dent of the cluster size and the occupation probability.
文摘为解决传统LEACH(Low Energy Adaptive Clustering Hierarchy)协议网络节点能量消耗高、存活数量少和生存寿命短等问题,提出了一种LEACH-AD改进方案。该算法引入最优簇头比率P值、加入距离因子、剩余能量因子和密度因子等因素更新的阈值公式进行分簇以及簇间的传输。实验结果表明,改进后的LEACH-AD协议在首个死亡节点、10%死亡节点以及全部死亡节点分别比原LEACH协议延长138轮、195轮、628轮。在能量消耗方面比原LEACH协议多持续了631轮,改进后的路由协议减少了网络节点的能量消耗量,从而有效延长了无线网络与传感节点的工作时间,这对无线监测系统的研究与开发意义重大。
文摘To the problem that it is hard to determine the clustering number and the abnormal points by using the clustering validity function, an effective clustering partition model based on the genetic algorithm is built in this paper. The solution to the problem is formed by the combination of the clustering partition and the encoding samples, and the fitness function is defined by the distances among and within clusters. The clustering number and the samples in each cluster are determined and the abnormal points are distinguished by implementing the triple random crossover operator and the mutation. Based on the known sample data, the results of the novel method and the clustering validity function are compared. Numerical experiments are given and the results show that the novel method is more effective.
文摘In the past 30 years, Chinese enterprises have been a hot topic of discussion and concern among the general public in terms of economic and social status, ownership structure, business mechanism, and management level. Solving the problem of employment for the people is an important prerequisite for their peaceful living and work, as well as a prerequisite and foundation for building a harmonious society. The employment situation of private enterprises has always been of great concern to the outside world, and these two major jobs have always occupied an important position in the employment field of China that cannot be ignored. With the establishment of the market economy system, individual and private enterprises have become important components of the socialist economy, making significant contributions to economic development and social progress. The rapid development of China’s economy, on the one hand, is the embodiment of the superiority of China’s socialist market economic system, and on the other hand, it is the role of the tertiary industry and private enterprises in promoting the national economy. Since the 1990s, China’s private enterprises have become a new economic growth point for local and even national countries, and are one of the important ways to arrange employment and achieve social stability. This paper studies the employment of private enterprises and individuals from the perspective of statistics, extracts relevant data from China statistical Yearbook, uses the relevant knowledge of statistics to process the data, obtains the conclusion and puts forward relevant constructive suggestions.
基金support from the National Natural Science Foundation of China (11402276)
文摘The cavitation cloud of different internal structures results in different collapse pressures owing to the interaction among bubbles. The internal structure of cloud cavitation is required to accurately predict collapse pressure. A cavitation model was developed through dimensional analysis and direct numerical simulation of collapse of bubble cluster. Bubble number density was included in proposed model to characterize the internal structure of bubble cloud. Implemented on flows over a projectile, the proposed model predicts a higher collapse pressure compared with Singhal model. Results indicate that the collapse pressure of detached cavitation cloud is affected by bubble number density.
基金Supported by the National Key Research and Development Program of China(No.2016YFB0201305)National Science and Technology Major Project(No.2013ZX0102-8001-001-001)National Natural Science Foundation of China(No.91430218,31327901,61472395,61272134,61432018)
文摘Clustering data with varying densities and complicated structures is important,while many existing clustering algorithms face difficulties for this problem. The reason is that varying densities and complicated structure make single algorithms perform badly for different parts of data. More intensive parts are assumed to have more information probably,an algorithm clustering from high density part is proposed,which begins from a tiny distance to find the highest density-connected partition and form corresponding super cores,then distance is iteratively increased by a global heuristic method to cluster parts with different densities. Mean of silhouette coefficient indicates the cluster performance. Denoising function is implemented to eliminate influence of noise and outliers. Many challenging experiments indicate that the algorithm has good performance on data with widely varying densities and extremely complex structures. It decides the optimal number of clusters automatically.Background knowledge is not needed and parameters tuning is easy. It is robust against noise and outliers.
