Data clustering is an important reserch field in data mining. The key of the clustering algorithm is the distance measure. In this paper,we put forward a new distance measure based on central symmetry. Then we apply i...Data clustering is an important reserch field in data mining. The key of the clustering algorithm is the distance measure. In this paper,we put forward a new distance measure based on central symmetry. Then we apply it to data clustering. The experimental studies prove the feasibility of this algorithm and get a satisfied result in face detection.展开更多
In order to mine production and security information from security supervising data and to ensure security and safety involved in production and decision-making,a clustering analysis algorithm for security supervising...In order to mine production and security information from security supervising data and to ensure security and safety involved in production and decision-making,a clustering analysis algorithm for security supervising data based on a semantic description in coal mines is studied.First,the semantic and numerical-based hybrid description method of security supervising data in coal mines is described.Secondly,the similarity measurement method of semantic and numerical data are separately given and a weight-based hybrid similarity measurement method for the security supervising data based on a semantic description in coal mines is presented.Thirdly,taking the hybrid similarity measurement method as the distance criteria and using a grid methodology for reference,an improved CURE clustering algorithm based on the grid is presented.Finally,the simulation results of a security supervising data set in coal mines validate the efficiency of the algorithm.展开更多
An advanced fuzzy C-mean （FCM） algorithm was proposed for the efficient regional clustering of multi-nodes interconnected systems. Due to various locational prices and regional coherencies for each node and point, m...An advanced fuzzy C-mean （FCM） algorithm was proposed for the efficient regional clustering of multi-nodes interconnected systems. Due to various locational prices and regional coherencies for each node and point, modified similarity measure was considered to gather nodes having similar characteristics. The similarity measure was needed to contain locafi0nal prices as well as regional coherency. In order to consider the two properties simultaneously, distance measure of fuzzy C-mean algorithm had to be modified. Regional clustering algorithm for interconnected power systems was designed based on the modified fuzzy C-mean algorithm. The proposed algorithm produces proper classification for the interconnected power system and the results are demonstrated in the example of IEEE 39-bus interconnected electricity system.展开更多
In free viewpoint video(FVV)and 3DTV,the depth image-based rendering method has been put forward for rendering virtual view video based on multi-view video plus depth(MVD) format.However,the projection with slightly d...In free viewpoint video(FVV)and 3DTV,the depth image-based rendering method has been put forward for rendering virtual view video based on multi-view video plus depth(MVD) format.However,the projection with slightly different perspective turns the covered background regions into hole regions in the rendered video.This paper presents a depth enhanced image summarization generation model for the hole-filling via exploiting the texture fidelity and the geometry consistency between the hole and the remaining nearby regions.The texture fidelity and the geometry consistency are enhanced by drawing texture details and pixel-wise depth information into the energy cost of similarity measure correspondingly.The proposed approach offers significant improvement in terms of 0.2dB PSNR gain,0.06 SSIM gain and subjective quality enhancement for the hole-filling images in virtual viewpoint video.展开更多
文摘Data clustering is an important reserch field in data mining. The key of the clustering algorithm is the distance measure. In this paper,we put forward a new distance measure based on central symmetry. Then we apply it to data clustering. The experimental studies prove the feasibility of this algorithm and get a satisfied result in face detection.
基金The National Natural Science Foundation of China(No.50674086)Specialized Research Fund for the Doctoral Program of Higher Education(No.20060290508)the Postdoctoral Scientific Program of Jiangsu Province(No.0701045B)
文摘In order to mine production and security information from security supervising data and to ensure security and safety involved in production and decision-making,a clustering analysis algorithm for security supervising data based on a semantic description in coal mines is studied.First,the semantic and numerical-based hybrid description method of security supervising data in coal mines is described.Secondly,the similarity measurement method of semantic and numerical data are separately given and a weight-based hybrid similarity measurement method for the security supervising data based on a semantic description in coal mines is presented.Thirdly,taking the hybrid similarity measurement method as the distance criteria and using a grid methodology for reference,an improved CURE clustering algorithm based on the grid is presented.Finally,the simulation results of a security supervising data set in coal mines validate the efficiency of the algorithm.
基金Work supported by the Second Stage of Brain Korea 21 ProjectsWork(2010-0020163) supported by Priority Research Centers Program through the National Research Foundation (NRF) funded by the Ministry of Education,Science and Technology of Korea
文摘An advanced fuzzy C-mean （FCM） algorithm was proposed for the efficient regional clustering of multi-nodes interconnected systems. Due to various locational prices and regional coherencies for each node and point, modified similarity measure was considered to gather nodes having similar characteristics. The similarity measure was needed to contain locafi0nal prices as well as regional coherency. In order to consider the two properties simultaneously, distance measure of fuzzy C-mean algorithm had to be modified. Regional clustering algorithm for interconnected power systems was designed based on the modified fuzzy C-mean algorithm. The proposed algorithm produces proper classification for the interconnected power system and the results are demonstrated in the example of IEEE 39-bus interconnected electricity system.
文摘In free viewpoint video(FVV)and 3DTV,the depth image-based rendering method has been put forward for rendering virtual view video based on multi-view video plus depth(MVD) format.However,the projection with slightly different perspective turns the covered background regions into hole regions in the rendered video.This paper presents a depth enhanced image summarization generation model for the hole-filling via exploiting the texture fidelity and the geometry consistency between the hole and the remaining nearby regions.The texture fidelity and the geometry consistency are enhanced by drawing texture details and pixel-wise depth information into the energy cost of similarity measure correspondingly.The proposed approach offers significant improvement in terms of 0.2dB PSNR gain,0.06 SSIM gain and subjective quality enhancement for the hole-filling images in virtual viewpoint video.
