NEURAL NETWORKS AS A TOOL FOR OBJECTIFYING THE ESTIMATES OF LABOR CAPACITY

The article examines existing approaches to assessing the worker’s labor potential. The advantages and disadvantages of each approach are analyzed. To improve the objectivity of labor force assessment systems it is recommended to use the apparatus of the theory of artificial neural networks. As a merit of this approach, the one can note the possibility of constructing sufficiently wide class of nonlinear models with implementation of automated procedures for selecting model parameters. To expand the capabilities of employee development systems it is recommended to use a two-component model of labor potential, which includes professional potential and development potential.

labor potential, labor potential assessment, subjective evaluation, objective evaluation, evaluation validation, neural network, set of reference assessments, information, innovative activity, objective approach.

Yudina L. N., Kosareva E. S. Neural networks as a tool for objectifying thr estimates of labor capacity // Business. Education. Law. Bulletin of Volgograd Business Institute. 2017. No. 2 (39). P. 110–113.