self organizing maps
Functional grouping and establishment of distribution patterns of invasive plants in China using self-organizing maps and indicator species analysis
... Self-organizing maps represent an artificial neural network model (Kohonen, 1982) aiming to clas- sify high dimensional data, performing a non-linear projection of multidimensional data space onto ...
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New developmental stages for common marmosets (Callithrix jacchus) using mass and age variables obtained by K-means algorithm and self-organizing maps (SOM)
... and self-organizing maps [16] are clustering methods that classify patterns without the need of previous information on data distribution, as occurs in supervised ...
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Research Article Geospatial Analysis of Extreme Weather Events in Nigeria (1985–2015) Using Self-Organizing Maps
... 2.3. Methodology. SOM are nonsupervised neural networks used for clustering, dimension reduction, and visualization. This research aims to achieve these three objectives by visually showing the areas with similar ...
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Self-organizing maps in the study of genetic diversity among irrigated rice genotypes
... presents self-organizing maps (SOM) as an alternative method to evaluate genetic diversity in plant breeding ...the maps. Regarding genotype arrangement and the group neighbors, maps ...
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Comparative analysis of model behaviour for flood prediction purposes using Self-Organizing Maps
... to their indices. With the exception of some very isolated occurrences there are no nodes on the map that are simul- taneously populated with model realizations from all three models. The same holds true for simultaneous ...
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Enhanced Data Topology Preservation with Multilevel Interior Growing Self-Organizing Maps
... Indeed, the proposed Multilevel Interior Growing Self- Organizing Maps (MIGSOM) increases the structure of the network by adding nodes where it is necessary. The network starts with a rectangular map ...
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SEISMIC INTERPRETATION OF SELF-ORGANIZING MAPS USING 2D COLOR DISPLAYS
... ABSTRACT. Classification without supervision of patterns into groups is formally called clustering. Depending on the application area these patterns are called data lists, observations or vectors. For exploration ...
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EXPLORATORY GEOSPATIAL DATA ANALYSIS USING SELF-ORGANIZING MAPS
... In this thesis a type of neural network, the Self-Organizing Maps (SOM), is used to perform data clustering and projection. It has been applied in a large variety of tasks, such as pattern ...
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A aplicação de self‐organizing maps na caracterização do universo geográfico dos serviços de correio
... 2 analisada encontraram-se várias técnicas (Chicco, Napoli, & Piglione, 2006) mas as que se destacaram foram o k-means e os SOM - Self Organizing-Maps (SOM), ambas são tipos de redes-neuronais ...
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Realistic three dimensional fitness landscapes generated by self organizing maps for the analysis of experimental HIV-1 evolution.
... estimated. Self-Organizing Maps (SOM) are a class of Artificial Neural Network (ANN) for the generation of topological ordered ...These maps were used for the visualization and study of the ...
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A framework for exploratory analysis of extreme weather events using geostatistical procedures and 3D self-organizing maps
... three-dimensional Self- Organizing Map to visualize the phenomenon from a global perspective, allowing identification and characterization of spatial patterns and homogeneous ...dimensional ...
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BUSINESS CUSTOMERS SEGMENTATION WITH THE USE OF K-MEANS AND SELF-ORGANIZING MAPS: AN EXPLORATORY STUDY IN THE CASE OF A SLOVENIAN BANK
... Yet, unless they want to be led into the wrong direction, practitioners have to be very careful about choosing and refining the appropriate variables on which to segment (Zimme[r] ...
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Quantifying Postural Control during Exergaming Using Multivariate Whole-Body Movement Data: A Self-Organizing Maps Approach.
... the self-organizing map (SOM) or Kohonen map, to compare and visual- ize coordination patterns in multi-dimensional data ...and organizing the information to a low-dimensional mapping ...
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ELECTROFACIES CHARACTERIZATION USING SELF-ORGANIZING MAPS
... ABSTRACT. The characterization of electrofacies is essential for reservoir modeling. However, this is a process that dependends on many variables, with errors and associated noise that interfere on visual interpretation. ...
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Visualization of Clusters in Geo-referenced Data Using Three-dimensional Self-Organizing Maps
... Let us consider the zone highlighted on both maps. In the 2D SOM, the zone is similar to the neighbourhood; on the contrary, the 3D SOM indicates there is a difference. Zone 1514 (indicated in the map) is, in ...
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ELECTROFACIES CLASSIFICATION OF PONTA GROSSA FORMATION BY MULTI-RESOLUTION GRAPH-BASED CLUSTERING (MRGC) AND SELF-ORGANIZING MAPS (SOM) METHODS
... Gamma ray (GR), sonic (DT) and long resistivity (RLN) logs were the input data and core simplified lithology are associated data used to estimate the accuracy and validate the mode[r] ...
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CARTO-SOM Cartogram creation using self-organizing maps
... oldest maps known in existence today were created around 2300 BC in ancient Babylonia on clay ...Today, maps continue to play a vital role in our society, supporting storage and communication of numerous ...
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Quím. Nova vol.35 número11
... a set of Matlab functions that can be used to develop and implement SOM neural networks, and which contains functions for creation, visualization and analysis of self-organizing maps. A SOM grid with ...
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Image Clustering Method Based on Density Maps Derived from Self-Organizing Mapping: SOM
... density maps derived from Self-Organizing Maps (SOM) is proposed together with a clarification of learning processes during a construction of ...
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Fingerprint Image Segmentation Using Haar Wavelet and Self Organizing Map
... Although some features have been chosen by researchers, finding simple and discriminative features is still a challenging problem. This paper proposed a new segmentation method based on block-wise features generated by ...
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