Open AccessA neural network application for the estimation of the probability of leaving a working place
Author(s) -
Alexandru Ene,
Ciprian Stirbu
Publication year - 2019
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/564/1/012087
Subject(s) - artificial neural network , abandonment (legal) , computer science , estimation , theme (computing) , process (computing) , artificial intelligence , order (exchange) , probability estimation , machine learning , economics , management , finance , political science , law , operating system
This article is about a topical theme, namely that of leaving a workplace, by an employee. The paper proposes that on the basis of input data, to make an estimate of the probability of leaving a job by a particular employee. In order to make such a prediction, the authors of the paper propose the use of artificial intelligence elements, namely artificial neural networks. Artificial neural networks have the ability to generalize, based on a history. The probability of abandonment of a job, is determined empirically, because there is not an exact mathematical formula. When we do not know the equation after which a particular process takes place, to make an estimation, neural networks are excellent tools.