نتایج جستجو برای: probabilistic clustering algorithms
تعداد نتایج: 473240 فیلتر نتایج به سال:
In this work, we aim to identify the mineralization areas for the next exploration phases. Thus, the probabilistic clustering algorithms due to the use of appropriate measures, the possibility of working with datasets with missing values, and the lack of trapping in local optimal are used to determine the multi-element geochemical anomalies. Four probabilistic clustering algorithms, namely PHC,...
this thesis is a study on insurance fraud in iran automobile insurance industry and explores the usage of expert linkage between un-supervised clustering and analytical hierarchy process(ahp), and renders the findings from applying these algorithms for automobile insurance claim fraud detection. the expert linkage determination objective function plan provides us with a way to determine whi...
the outcome of this research is a practical framework for “idea generation phase of new product development process based on customer knowledge”. in continue, the mentioned framework implemented in a part of iran n.a.b market and result in segmenting and profiling this market. also, the critical new product attributes and bases of communication message and promotion campaigns extracted. we have...
Correlations may exist among adjacent edges in various probabilistic graphs. As one of the basic mining techniques, graph clustering is widely used in exploratory data analysis, such as data compression, information retrieval, image segmentation, etc. Graph clustering aims to divide data into clusters according to their similarities, and a number of algorithms have been proposed for clustering ...
Spatial clustering has been widely applied in various applications, especially in remote sensing technology. Clustering the geographical nature of the remote sensing imagery is challenging due to its wide and dense spatial distribution. Renowned clustering algorithms such as k-means and other probabilistic clustering algorithms have been reported in the literature. However, they are not robust ...
Spatial clustering has been widely applied in various applications, especially in remote sensing technology. Clustering the geographical nature of the remote sensing imagery is challenging due to its wide and dense spatial distribution. Renowned clustering algorithms such as k-means and other probabilistic clustering algorithms have been reported in the literature. However, they are not robust ...
Spatial clustering has been widely applied in various applications, especially in remote sensing technology. Clustering the geographical nature of the remote sensing imagery is challenging due to its wide and dense spatial distribution. Renowned clustering algorithms such as k-means and other probabilistic clustering algorithms have been reported in the literature. However, they are not robust ...
Spatial clustering has been widely applied in various applications, especially in remote sensing technology. Clustering the geographical nature of the remote sensing imagery is challenging due to its wide and dense spatial distribution. Renowned clustering algorithms such as k-means and other probabilistic clustering algorithms have been reported in the literature. However, they are not robust ...
Spatial clustering has been widely applied in various applications, especially in remote sensing technology. Clustering the geographical nature of the remote sensing imagery is challenging due to its wide and dense spatial distribution. Renowned clustering algorithms such as k-means and other probabilistic clustering algorithms have been reported in the literature. However, they are not robust ...
نمودار تعداد نتایج جستجو در هر سال
با کلیک روی نمودار نتایج را به سال انتشار فیلتر کنید