Analysis of Complex Systems using the Self

The Self-Organizing Map (SOM) is a powerful neural network method for the analysis and visualization of high-dimensional data. It maps nonlinear statistical relationships between high-dimensional input data into simple geometric relationships on a usually two-dimensional grid. The mapping roughly preserves the most important topological and metric relationships of the original data elements and, thus, inherently clusters the data. The need for eecient data visualization and clustering is often faced, for instance, in the analysis of various engineering problems. In this paper, the use of the SOM based methods in analysis, monitoring and modeling of complex industrial processes is discussed.