Using neural networks and machine learning to identify obstructive techniques in communications in large scale systems implementation projects for Industry 4

Smirnov Sergey Pavlovich

Less than a third of the global volume of completed projects are completely successful. As one of the key problems that actually kill projects, the problem of poor-quality project communications is described in the literature. The paper presents the results of the analysis of the possibility of using neural networks and machine learning methods to automate the recognition of obstructive techniques in project communications, which was not previously described in the literature.

Keywords:project management, project communications, project risks, obstructive techniques, neural networks, machine learning.