A clustering algorithm for semi-supervised affinity propagation based on layered combination is proposed in this paper in light of existing flaws. To improve accuracy of the algorithm,it introduces the idea of layered...A clustering algorithm for semi-supervised affinity propagation based on layered combination is proposed in this paper in light of existing flaws. To improve accuracy of the algorithm,it introduces the idea of layered combination, divides an affinity propagation clustering( APC) process into several hierarchies evenly,draws samples from data of each hierarchy according to weight,and executes semi-supervised learning through construction of pairwise constraints and use of submanifold label mapping,weighting and combining clustering results of all hierarchies by combined promotion. It is shown by theoretical analysis and experimental result that clustering accuracy and computation complexity of the semi-supervised affinity propagation clustering algorithm based on layered combination( SAP-LC algorithm) have been greatly improved.展开更多
为使AP算法对图像进行聚类时充分考虑不同尺度的特征及有效利用未标记数据的特征,提出了结合特征金字塔网络的半监督AP聚类算法(Semi-supervised AP clustering Based on Feature Pyramid Networks,FPNSAP)。FPNSAP算法使用改进的特征...为使AP算法对图像进行聚类时充分考虑不同尺度的特征及有效利用未标记数据的特征,提出了结合特征金字塔网络的半监督AP聚类算法(Semi-supervised AP clustering Based on Feature Pyramid Networks,FPNSAP)。FPNSAP算法使用改进的特征金字塔网络来获得图像不同尺度的特征图,对不同大小的特征图进行融合,获得图像的高级语义特征,识别不同大小、不同实例的目标;k近邻标记更新策略可以动态增加标记数据集样本数量,充分利用未标记数据的特征,提高AP算法的聚类性能。FPNSAP算法与四个经典算法(FCH、SAP、DCN和DFCM)在Fashion-MNIST、YaleB和CIFAR-10数据集上进行实验对比,结果表明,FPNSAP算法具有较高的聚类性能,同时算法的鲁棒性更好。展开更多
Large and complex construction projects lace risk trom various sources and the successlul completion of such projects depends on effective risk management. This study investigates the risk faced by Chinese firms parti...Large and complex construction projects lace risk trom various sources and the successlul completion of such projects depends on effective risk management. This study investigates the risk faced by Chinese firms participating in constructing AP 1000 nuclear power plants in China. AP 1000 nuclear reactors are new, Generation III＋ reactors designed by Westinghouse and to be built first in China. The semi-structured interview approach is used to elicit information from experts involved in the AP1000 projects in China. Based on the interviews, various sources of risk are identified. In addition to general risks that megaprojects normally face, there are unique risks that arise from various sources such as technological, political, organizational, and individual personnel risks. Risk management strategies are proposed to manage general and unique risks identified in the study. The findings of this study would be helpful for Chinese companies involved in the construction of AP 1000 nuclear power plants to mitigate the risks associated with the projects.展开更多
基金the Science and Technology Research Program of Zhejiang Province,China(No.2011C21036)Projects in Science and Technology of Ningbo Municipal,China(No.2012B82003)+1 种基金Shanghai Natural Science Foundation,China(No.10ZR1400100)the National Undergraduate Training Programs for Innovation and Entrepreneurship,China(No.201410876011)
文摘A clustering algorithm for semi-supervised affinity propagation based on layered combination is proposed in this paper in light of existing flaws. To improve accuracy of the algorithm,it introduces the idea of layered combination, divides an affinity propagation clustering( APC) process into several hierarchies evenly,draws samples from data of each hierarchy according to weight,and executes semi-supervised learning through construction of pairwise constraints and use of submanifold label mapping,weighting and combining clustering results of all hierarchies by combined promotion. It is shown by theoretical analysis and experimental result that clustering accuracy and computation complexity of the semi-supervised affinity propagation clustering algorithm based on layered combination( SAP-LC algorithm) have been greatly improved.
文摘为使AP算法对图像进行聚类时充分考虑不同尺度的特征及有效利用未标记数据的特征,提出了结合特征金字塔网络的半监督AP聚类算法(Semi-supervised AP clustering Based on Feature Pyramid Networks,FPNSAP)。FPNSAP算法使用改进的特征金字塔网络来获得图像不同尺度的特征图,对不同大小的特征图进行融合,获得图像的高级语义特征,识别不同大小、不同实例的目标;k近邻标记更新策略可以动态增加标记数据集样本数量,充分利用未标记数据的特征,提高AP算法的聚类性能。FPNSAP算法与四个经典算法(FCH、SAP、DCN和DFCM)在Fashion-MNIST、YaleB和CIFAR-10数据集上进行实验对比,结果表明,FPNSAP算法具有较高的聚类性能,同时算法的鲁棒性更好。
文摘Large and complex construction projects lace risk trom various sources and the successlul completion of such projects depends on effective risk management. This study investigates the risk faced by Chinese firms participating in constructing AP 1000 nuclear power plants in China. AP 1000 nuclear reactors are new, Generation III＋ reactors designed by Westinghouse and to be built first in China. The semi-structured interview approach is used to elicit information from experts involved in the AP1000 projects in China. Based on the interviews, various sources of risk are identified. In addition to general risks that megaprojects normally face, there are unique risks that arise from various sources such as technological, political, organizational, and individual personnel risks. Risk management strategies are proposed to manage general and unique risks identified in the study. The findings of this study would be helpful for Chinese companies involved in the construction of AP 1000 nuclear power plants to mitigate the risks associated with the projects.
