Neural networks represent the core technology we use for data-based modeling. We have advanced this technology with the development of hybrid models, enabling us to integrate existing process knowledge. An additional advantage of hybrid models is that they can be used outside the influence parameter ranges which are covered by the measured data. We also combine these methods with tailored data mining algorithms developed specifically for the process industries.

We have a wide range of high-performance software tools for data acquisition, data preprocessing and modeling. These include both commercial products and in-house developments:

Daisy             data acquisition
DVV-Tool      data preprocessing
Daminex       data mining
K.wiz™          data analysis and data preprocessing
HybridTool    hybrid modeling
NNTool          modelng with neural networks
OPAL             model visualization, optimization