为了解决模糊聚类-矢量量化算法都是强迫模糊分区转变为Crisp集合,降低码本质量,使重构图像丢失了丰富的边缘纹理信息;且其计算代价较高,以及严重依赖初始化等不足。提出了竞争聚类耦合码字定向移动的图像重构模糊矢量量化算法。引入竞...为了解决模糊聚类-矢量量化算法都是强迫模糊分区转变为Crisp集合,降低码本质量,使重构图像丢失了丰富的边缘纹理信息;且其计算代价较高,以及严重依赖初始化等不足。提出了竞争聚类耦合码字定向移动的图像重构模糊矢量量化算法。引入竞争聚类,基于C均值和模糊C均值,设计最优目标函数;结合拉格朗日乘子,推导出最优目标函数的聚类中心和隶属度的求解模型;定义迁移规则,构造了码字定向移动机制,使得小簇群向大簇群移动,形成更大的簇群;以失真度和相似度为评估准则,构造量化反馈机制,优化重构图像。仿真结果显示:与其他矢量量化机制相比,本文算法的编码图像相似度更高,PSNR(peak signal to noise ratio)最高,得到的重构图像质量最佳;且本文算法的时间成本最低。展开更多
We propose a novel scheme based on clustering analysis in color space to solve text segmentation in complex color images. Text segmentation includes automatic clustering of color space and foreground image generation....We propose a novel scheme based on clustering analysis in color space to solve text segmentation in complex color images. Text segmentation includes automatic clustering of color space and foreground image generation. Two methods are also proposed for automatic clustering: The first one is to determine the optimal number of clusters and the second one is the fuzzy competitively clustering method based on competitively learning techniques. Essential foreground images obtained from any of the color clusters are combined into foreground images. Further performance analysis reveals the advantages of the proposed methods.展开更多
From the perspective of tourism competitiveness,the paper takes 12 island counties of China as the research object,and applies the method of factor analysis to study their competitiveness.The result shows that Putuo a...From the perspective of tourism competitiveness,the paper takes 12 island counties of China as the research object,and applies the method of factor analysis to study their competitiveness.The result shows that Putuo and Dinghai are more competitive while Pingtan and Nan'ao are less competitive.Finally,the 12 island counties are divided into four styles:first-class competitive county (Putuo),seond-class competitive counties (Dinghai,Yuhuan),third-class competitive counties (Chongming,Daishan,Changdao,Changhai and Shengsi),fourth-class competitive counties (Dongshan,Dongtou,Pingtan and Nan'ao) by cluster analysis.The classification of island counties is to clear their relative position,then to promote their development.展开更多
Clustering is one of the most widely used data mining techniques that can be used to create homogeneous clusters.K-means is one of the popular clustering algorithms that,despite its inherent simplicity,has also some m...Clustering is one of the most widely used data mining techniques that can be used to create homogeneous clusters.K-means is one of the popular clustering algorithms that,despite its inherent simplicity,has also some major problems.One way to resolve these problems and improve the k-means algorithm is the use of evolutionary algorithms in clustering.In this study,the Imperialist Competitive Algorithm(ICA) is developed and then used in the clustering process.Clustering of IRIS,Wine and CMC datasets using developed ICA and comparing them with the results of clustering by the original ICA,GA and PSO algorithms,demonstrate the improvement of Imperialist competitive algorithm.展开更多
This paper introduces data mining technology in enterprise competitive intelligence system; and then introduced theoretical foundation and main clustering method of cluster analysis. The article emphasis on the FCM al...This paper introduces data mining technology in enterprise competitive intelligence system; and then introduced theoretical foundation and main clustering method of cluster analysis. The article emphasis on the FCM algorithm and principle and described implementation steps, and proposed the improvement FCM algorithm based on K mean particle size; finally, realize the design and implementation of enterprise competitive intelligence analysis and mining service system, and the improved FCM algorithm is applied in the system.展开更多
文摘为了解决模糊聚类-矢量量化算法都是强迫模糊分区转变为Crisp集合,降低码本质量,使重构图像丢失了丰富的边缘纹理信息;且其计算代价较高,以及严重依赖初始化等不足。提出了竞争聚类耦合码字定向移动的图像重构模糊矢量量化算法。引入竞争聚类,基于C均值和模糊C均值,设计最优目标函数;结合拉格朗日乘子,推导出最优目标函数的聚类中心和隶属度的求解模型;定义迁移规则,构造了码字定向移动机制,使得小簇群向大簇群移动,形成更大的簇群;以失真度和相似度为评估准则,构造量化反馈机制,优化重构图像。仿真结果显示:与其他矢量量化机制相比,本文算法的编码图像相似度更高,PSNR(peak signal to noise ratio)最高,得到的重构图像质量最佳;且本文算法的时间成本最低。
基金国家自然科学基金重点项目(National Natural Science Foundation of China No.60634020)教育部博士点基金项目(the Ph.D. Programs Foundation of Ministry of Education of China No.20060532026)
文摘We propose a novel scheme based on clustering analysis in color space to solve text segmentation in complex color images. Text segmentation includes automatic clustering of color space and foreground image generation. Two methods are also proposed for automatic clustering: The first one is to determine the optimal number of clusters and the second one is the fuzzy competitively clustering method based on competitively learning techniques. Essential foreground images obtained from any of the color clusters are combined into foreground images. Further performance analysis reveals the advantages of the proposed methods.
基金supported by a grant from Shandong Social Science Planning Project in 2010 (Grant No:10CJGJ22)Ocean University of China Young Teachers Special Fund Project in 2010 (Grant No:201013070)
文摘From the perspective of tourism competitiveness,the paper takes 12 island counties of China as the research object,and applies the method of factor analysis to study their competitiveness.The result shows that Putuo and Dinghai are more competitive while Pingtan and Nan'ao are less competitive.Finally,the 12 island counties are divided into four styles:first-class competitive county (Putuo),seond-class competitive counties (Dinghai,Yuhuan),third-class competitive counties (Chongming,Daishan,Changdao,Changhai and Shengsi),fourth-class competitive counties (Dongshan,Dongtou,Pingtan and Nan'ao) by cluster analysis.The classification of island counties is to clear their relative position,then to promote their development.
文摘Clustering is one of the most widely used data mining techniques that can be used to create homogeneous clusters.K-means is one of the popular clustering algorithms that,despite its inherent simplicity,has also some major problems.One way to resolve these problems and improve the k-means algorithm is the use of evolutionary algorithms in clustering.In this study,the Imperialist Competitive Algorithm(ICA) is developed and then used in the clustering process.Clustering of IRIS,Wine and CMC datasets using developed ICA and comparing them with the results of clustering by the original ICA,GA and PSO algorithms,demonstrate the improvement of Imperialist competitive algorithm.
文摘This paper introduces data mining technology in enterprise competitive intelligence system; and then introduced theoretical foundation and main clustering method of cluster analysis. The article emphasis on the FCM algorithm and principle and described implementation steps, and proposed the improvement FCM algorithm based on K mean particle size; finally, realize the design and implementation of enterprise competitive intelligence analysis and mining service system, and the improved FCM algorithm is applied in the system.
