Data publishing techniques have led to breakthroughs in several areas. These tools provide a promising direction. However, when they are applied private or sensitive data such as patient medical records, the published may divulge critical information. In order address this issue, we propose differential method (SSKM_DP) based on SFLA-Kohonen network, which perturbs attributes maximum informatio...

This paper describes the application of two different neural network types for stock price prediction. The prediction is carried out by Kohonen self-organizing maps and error backpropagation algorithm. Both experimental networks deal with price change intervals in contradiction to precise value prediction. The results are presented and its comparative analysis is performed in this paper, as wel...

The amount of collected and stored information is growing every day in several areas of knowledge and data mining techniques are applied to these datasets in order to extract useful knowledge. One or another algorithm, or the same algorithm with different attributes, can lead to different results due to the dataset diversity. To solve this problem, machines committees methods were developed. A ...

The Self-Organizing Map (SOM) is an unsupervised neural network introduced in the 80’s by Teuvo Kohonen. In this paper, we propose a method of simultaneously using two kinds of SOM whose features are different (the nSOM method). Namely, one is distributed in the area at which input data are concentrated, and the other self-organizes the whole of the input space. The competing behavior of the tw...