And what's so special about ANDATA's approach?

Data-Mining or numerical simulation is also done by quite a lot of other's. What's the difference to ANDATA?

The main difference of ANDATA to others is the skilled combination of methods from the fields of SoftComputing respectively Machine Learning with numerical simulation and the support with requirement driven design process models from software engineering.

Often these fields are propagated and pushed only isolated from each other. But looking into the depth these fields can extremly leverage the solution potentials for complex problems, when using them in combination.

SoftComputing and Machine Learning are already efficient methods to tackle complex problems. Numerical simulation is well suited to fill up the training database in an appropriate way. Vice versa Data Mining helps to extract and gain maximum knowledge and comprehensive understanding of complex systems from simulation data.

Example based approaches are again perfectly capable of being combined with according design process models. When representing the functional system requirements with examples from test and/or simulations they can directly be trainied instead of manually constructing a solution draft. Hereby the functional requirements are turned into a mathematical model, which in return can be used to constructively deal with potential conflicts in the requirements. Requirement management then becomes an active constructive process instead of just formally administrating them.

Last update on 2016-12-04 by Andreas Kuhn.

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