Insights on the interpretation of SOM and U-Matrices with an example clustering based in oceanographic data
نویسندگان
چکیده
In this paper a process for the detection of clusters in oceanographic data is described. The application to oceanographic data is relevant as it allows the improvement of the understanding of the phenomena occurring in the Portuguese coast. Additionally, the application also illustrates how the self-organizing maps maybe used to explore and explain clusters, especially emphasizing the relevance of the visualization process in this context.
منابع مشابه
Electrofacies clustering and a hybrid intelligent based method for porosity and permeability prediction in the South Pars Gas Field, Persian Gulf
This paper proposes a two-step approach for characterizing the reservoir properties of the world’s largest non-associated gas reservoir. This approach integrates geological and petrophysical data and compares them with the field performance analysis to achieve a practical electrofacies clustering. Porosity and permeability prediction is done on the basis of linear functions, succeeding the elec...
متن کاملNGTSOM: A Novel Data Clustering Algorithm Based on Game Theoretic and Self- Organizing Map
Identifying clusters is an important aspect of data analysis. This paper proposes a noveldata clustering algorithm to increase the clustering accuracy. A novel game theoretic self-organizingmap (NGTSOM ) and neural gas (NG) are used in combination with Competitive Hebbian Learning(CHL) to improve the quality of the map and provide a better vector quantization (VQ) for clusteringdata. Different ...
متن کاملDistance Matrix Based Clustering of the Self-Organizing Map
Clustering of data is one of the main applications of the Self-Organizing Map (SOM). U-matrix is a commonly used technique to cluster the SOM visually. However, in order to be really useful, clustering needs to be an automated process. There are several techniques which can be used to cluster the SOM autonomously, but the results they provide do not follow the results of U-matrix very well. In ...
متن کاملApplication of a Self-Organizing Map for Clustering the Groundwater Quality in Kerman Province and Assessment its Suitability for Drinking and Irrigation Purposes
Evaluation of groundwater hydro chemical characteristics is necessary for planning and water resources management in terms of quality. In the present study, a self-organizing map (SOM) clustering technique was used to recognize the homogeneous clusters of hydro chemical parameters in water resources (including well, spring and qanat) of Kerman province; then, the quality classification of groun...
متن کاملDeveloping A Fault Diagnosis Approach Based On Artificial Neural Network And Self Organization Map For Occurred ADSL Faults
Telecommunication companies have received a great deal of research attention, which have many advantages such as low cost, higher qualification, simple installation and maintenance, and high reliability. However, the using of technical maintenance approaches in Telecommunication companies could improve system reliability and users' satisfaction from Asymmetric digital subscriber line (ADSL) ser...
متن کامل