Abstract
Today, the management of complex innovative projects to create new aircraft is carried out in the conditions of uncertainty, which is due to the lack of “high-quality” (complete, accurate, consistent, etc.) data on their internal and external environment. In this situation, to support the adoption of project decisions, it is advisable to use an approach based on the identification and assessment of NON-factors that have a negative meaning in natural language and deny one of the basic properties of formal systems. The authors propose a procedure for analyzing NON-factors in project risk management, based on the assessment of uncertain factors of internal and external project environment using various methods of data mining (particularly, neural fuzzy classifier, fuzzy pyramidal networks, fuzzy logic methods, fuzzy Kalman filtering algorithms). Using the proposed approach will increase the validity of decisions on the viability of such innovative projects and a set of measures for risk management.
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