نتایج جستجو برای: kessel clustering algorithm
تعداد نتایج: 824731 فیلتر نتایج به سال:
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...
Pressure–volume–temperature properties are very important in the reservoir engineering computations. There are many empirical approaches for predicting various PVT properties based on empirical correlations and statistical regression models. Last decade, researchers utilized neural networks to develop more accurate PVT correlations. These achievements of neural networks open the door to data mi...
In this paper, a dynamic evidential clustering algorithm (DEC) is introduced to address the computational burden of existing methods. To derive such solution, an FCM-like objective function first employed and minimized obtain support levels real singletons (specific) clusters which query objects belong, then initially adaptively assigned outlier, precise or imprecise one via new rule-based on c...
Clustering is one of the main tasks in data mining, which means grouping similar samples. In general, there is a wide variety of clustering algorithms. One of these categories is density-based clustering. Various algorithms have been proposed for this method; one of the most widely used algorithms called DBSCAN. DBSCAN can identify clusters of different shapes in the dataset and automatically i...
Fuzzy clustering methods are conveniently employed in constructing a fuzzy model of a system, but they need to tune some parameters. In this research, FCM is chosen for fuzzy clustering. Parameters such as the number of clusters and the value of fuzzifier significantly influence the extent of generalization of the fuzzy model. These two parameters require tuning to reduce the overfitting in the...
Clustering is the process of division of a dataset into subsets that are called clusters, so that objects within a cluster are similar to each other and different from objects of the other clusters. So far, a lot of algorithms in different approaches have been created for the clustering. An effective choice (can combine) two or more of these algorithms for solving the clustering problem. Ensemb...
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