In the process of making a decision on the inclusion of an applicant in the project team, it is proposed to take into account his project results targeting (PRT). The article describes the conceptual basis for identifying people’s focus on achieving the results of significant projects based on the use of virtual reality tools and the capabilities of fuzzy inference systems. At the same time, to configure the parameters of the membership functions of the fuzzy inference system and the values of the individual inferences of the fuzzy rules, the use of a neural-fuzzy network is proposed. To get a training sample, the participants of the teams of implemented projects will need to pass a series of tests using virtual reality tools. According to the proposed concept, persons with high PRT will be primarily recommended for inclusion in the team of project performers.
The project implementation effectiveness in creating digital smart agriculture systems depends on the correct selection of performers. Considering personal priorities makes it possible to increase the validity of decision-making regarding the employment of specific individuals for the implementation of IT projects in the agro-industrial sector. Personal priorities are internal, hidden characteristics that have an effect on the process of long-term joint work and interaction in various situations that arise in the team. The identification of the analyzed individual’s personal priorities is proposed to be reduced to solving the classification problem based on the analysis of person’s text Internet traces using neural network technologies of natural language processing. As a training sample, it is proposed to use a set of text document vectors and the corresponding marks of personal priority classes. In the process of identifying the personal priorities classes, it is required to create an appropriate text array based on parsing and processing of text messages published on the Internet by the analyzed person. Next, from the resulting text array, a text vector of the document must be formed, which then needs to be submitted to the input of the neural network. It is assumed that the mark of the analyzed individual’s personal priority class will be displayed in the output layer of neurons.
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