... of SelfOrganizingMap (SOM) which is a type of unsupervised Artificial Neural Network (ANN), as an aid to Maximal Ratio Combining (MRC) in order to improve bit error rate (BER) values of ...
... of SelfOrganizingMap (SOM) to seg- ment individuals based on their credit ...information. SOM is an unsupervised machine learning method that reduces data complexity and ...
... the SelfOrganizingMap are provided and it is also include of the example from the Matlab that had been try to give some explanation to use SOM technique for the clustering and to diagnosis ...
... classical SOM called Growing Hierarchical SOM ...Kohenen’s SelfOrganizingMap to organize Web documents into a two dimensional map according their document ...Kohonen’s ...
... as Selforganizingmap and Neural Network to detect the various tissues like white matter, gray matter and cerebral spinal fluid for a given magnetic resonance image data set and also provide ...
... Since Self-organizingmap has a 2-dimensional topology, the relations between centers of 19-dimensional clusters have been illustrated in a 2-dimensional ...
... In this paper we suggest the novel move toward for the detection of brain tumor. Here we use the classification technique of K-nearest neighbor (KNN) and for ignoring the error of the dataset image SOM ...
... the SOM algorithm. The SOM algorithm classification of both AOD and ÅE is attributed to anthropo- genic influences among them land clearance, deforestation activities and bio- mass burning that dominate the ...
... classes. Self-OrganizingMap (SOM) was used to cluster datasets of CK metrics values that were extracted from three different java-based ...how SOM can be applied on software CK metrics ...
... on SOM as clustering, feature selection and classification, is ...introduced. SOM is employed by redesigning its several training phases to cope with the complex nature of DNA sequences, and integrating ...
... Neurons in a spherical SOM are commonly placed in a geodesic dome, a type of quasi-regular polyhedron [5]. A geodesic dome is an approximated sphere constructed by halving each edge of a regular polyhedron, thus ...
... on self-organizingmap ...using SOM is that the method can automatically (self-organizing) clusters ...The SOM algorithm also can be applied to a large scale of social ...
... Nowadays, there are many researchers study about design and concepts of selforganizing maps in smart grid. The analysis also focus on the cascading failure analysis in multi-contingency scenarios has been ...
... The SOM can be reliably applied in most of the hydrological study, especially in dealing with missing values on rainfall ...used. Self-organizingmap (SOM) is then applied to identify ...
... use SOM for clustering using the log file have encouraged this study to explore the performance of SOM in order to find the most significant clustering result that able to discover some hidden pattern in ...
... as SelfOrganizing Feature MAPS. The Self-OrganizingMap was evolved by Professor Tevo Kohonen and has been proven useful in many ...by SOM in unsupervised ...
... algorithm, self-organizing maps (SOM), and finally apply the Principal Component Analysis (PCA) for avoid the unwanted values, adjust the data with help of log transform, for clustering genes and ...
... of SOM using different competitive learning algorithms to find the optimum conditions to classify measured PD activities into underlying insulation defects or source that generate ...and SOM quality ...
... Surigao del Norte is a province of the Philippines located in the Caraga region of Mindanao between 125º15’ to 126º15’ east longitude and 9º18’ to 10º30’ north latitude [23]. It is bounded on the north and east by the ...
... customer relationship management (i.e. customer segmentation) into intelligent technology to predict the default. This study aimed to build a two-stage default predicted model by using self-organizing ...