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CDS Data Analysis Inc. focuses on data exploitation within the context in which the collected data have been observed.

Based on research in fuzzy logic and evolutionary algorithms, we develop programs that autonomously - without any human interaction - develop complex cybernetic systems that simulate entire systems in which the available data have been observed.
These systems are used to forecast data and derive prognoses.

Standard approaches of Data Analysis focus on statistical evaluation of data using a priori assumptions to determine underlying correlations. Linear or non-linear regression analysis is employed to determine models in order to explain and forecast data in varied environments.

Our approach focuses on the development of complex influence systems modelling the interaction of domains relevant to the context of the observed variables.

Standard approaches in Data Analysis are context based, our approaches are

Context Integrated


CDS Data Analysis Inc. provides:
For the following table three different approaches were employed to forecast the development of a major stock index.
The forecasts were then compared with the actual outcome and the standard error and confidence values determined. All data were provided by an investment company that also provided the results for the Artificial Neural Network.