Abstract
The problem of predicting project actual results deviation from the results expected at the pre-project planning stage is considered. The efficiency of neural network-based models is analyzed. It is proposed to use the neural-evolution approach for problem solving and to use PDRI and project failure risk values as informative criterions. The criterion of results informativity is proposed. The method of predicting actual project results deviation from the results expected at the pre-project planning stage is presented.
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