Abstract
In the real world, it is not always true that neighboring houses are physically adjacent or close to each other. in other words, “neighbors” are not always “true neighbors” In this study, we propose a new Self-Organizing Map (SOM) algorithm, SOM with False-Neighbor degree between neurons (called FN-SOM). The behavior of FN-SOM is investigated with learning for various input data. We confirm that FN-SOM can obtain a more effective map reflecting the distribution state of input data than the conventional SOM and Growing Grid.
