Abstract
Today, the implementation of complex innovative projects to create mechanical engineering products is a priority area of state policy. The high technical complexity, the huge number of participants, the duration of the implementation of such projects require the use of effective decision support tools. However, the existing mathematical methods do not take into account this specificity. This leads to the need to develop a conceptually new approach to solving the scientific task. The article proposes a procedure for analyzing the prospects of implementing the complex innovative project based on an assessment of the innovative potential of its participants and the external environment. It is based on the integrated application of data mining methods (fuzzy Kalman filter, growing pyramidal networks, fuzzy logic algorithms) that allow solving various tasks of supporting project decisions.
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