نتایج جستجو برای: clustering
تعداد نتایج: 102936 فیلتر نتایج به سال:
In current study, a particle swarm clustering method is suggested for clustering triangular fuzzy data. This clustering method can find fuzzy cluster centers in the proposed method, where fuzzy cluster centers contain more points from the corresponding cluster, the higher clustering accuracy. Also, triangular fuzzy numbers are utilized to demonstrate uncertain data. To compare triangular fuzzy ...
An ensemble clustering has been considered as one of the research approaches in data mining, pattern recognition, machine learning and artificial intelligence over the last decade. In clustering, the combination first produces several bases clustering, and then, for their aggregation, a function is used to create a final cluster that is as similar as possible to all the cluster bundles. The inp...
clustering is one of the known techniques in the field of data mining where data with similar properties is within the set of categories. k-means algorithm is one the simplest clustering algorithms which have disadvantages sensitive to initial values of the clusters and converging to the local optimum. in recent years, several algorithms are provided based on evolutionary algorithms for cluster...
Swarm Intelligence (SI) is an innovative artificial intelligence technique for solving complex optimization problems. Data clustering is the process of grouping data into a number of clusters. The goal of data clustering is to make the data in the same cluster share a high degree of similarity while being very dissimilar to data from other clusters. Clustering algorithms have been applied to a ...
in this paper an application of gustafson-kessel clustering algorithm is presented to create a fault detection map (fdm). five post-stack seismic attributes are extracted from a desired seismic time slice related to 3d seismic data of a gas field located in southwest of iran. to find the optimal cluster numbers, two frequently used clustering validity measures, i.e. sc and xb, are used and then...
knowing the fact that the main weakness of the most standard methods including k-means and hierarchical data clustering is their sensitivity to initialization and trapping to local minima, this paper proposes a modification of convex data clustering in which there is no need to be peculiar about how to select initial values. due to properly converting the task of optimization to an equivalent...
this paper compares clusters of aligned persian and english texts obtained from k-means method. text clustering has many applications in various fields of natural language processing. so far, much english documents clustering research has been accomplished. now this question arises, are the results of them extendable to other languages? since the goal of document clustering is grouping of docum...
Clustering is one of the main techniques in data mining. Clustering is a process that classifies data set into groups. In clustering, the data in a cluster are the closest to each other and the data in two different clusters have the most difference. Clustering algorithms are divided into two categories according to the type of data: Clustering algorithms for numerical data and clustering algor...
search pointers organize the main part of the application on the internet. however, because of information management hardware, high volume of data and word similarities in different fields the most answers to the user s’ questions aren`t correct. so the web graph clustering and cluster placement in corresponding answers helps user to achieve his or her intended results. community (web communit...
بررسی خصوصیات مورفولوژیکی و دانه های گرده در جمعیت های 12 گونه achillea از سه بخش santolinoidea ، millefolium و filipendulinae انجام گرفت. تعداد 33 صفت ریختی شامل 13 صفت کمی و 20 صفت کیفی برسی شدند. آنالیز واریانس وجود اختلاف معنی دار را در بسیاری از صفات کمی در میان جمعیت ها و گونه های مطالعه شده نشان داد. تجزیه خوشه ای بر اساس صفات کمی و نیز توام با صفات کیفی، جدایی جمعیت های یک گونه را از د...
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