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
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;
Conference_Titel :
Neural Networks (IJCNN), The 2010 International Joint Conference on
Conference_Location :
Barcelona
Print_ISBN :
978-1-4244-6916-1
DOI :
10.1109/IJCNN.2010.5596795
