DocumentCode
2495142
Title
Clustering using SOFM and genetic algorithm
Author
Salas, J. C Palomares ; Pérez, A. Agüera ; De la Rosa, J.J.G. ; Ramiro, J.G.
Author_Institution
Res. Group PAIDI-TIC-168: Comput. Instrum. & Ind. Electron. (ICEI), Univ. of Cadiz, Algeciras, Spain
fYear
2010
fDate
18-23 July 2010
Firstpage
1
Lastpage
6
Abstract
In this analysis a process to demarcate areas with analogous wind conditions is shown. For this purpose a dispersion graph between the wind directions will be traced for all stations placed in the studied zone. These distributions will be compared among themselves using the centroids extracted with SOFM algorithm. This information will be used to build a matrix, allowing us working simultaneously with all relations. By permutation of elements in this matrix it is possible to group relationed stations.
Keywords
genetic algorithms; geophysics computing; graph theory; learning (artificial intelligence); pattern clustering; self-organising feature maps; SOFM algorithm; clustering analysis technique; clustering method; dispersion graph; genetic algorithm; self-organizing feature map; unsupervised learning; Bioinformatics; Classification algorithms; Clustering algorithms; Gallium; Genomics; Lattices; Neurons;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks (IJCNN), The 2010 International Joint Conference on
Conference_Location
Barcelona
ISSN
1098-7576
Print_ISBN
978-1-4244-6916-1
Type
conf
DOI
10.1109/IJCNN.2010.5596795
Filename
5596795
Link To Document