Brief Analysis of the Evolution of Female Employees in Recent Years. Research Using Mathematical Modelling

Abstract

The numbers of male against female employment are still an actual and sensitive issue. Thus, the forecast of male and female employment evolution can offer the possibility to make decisions for the minimization of female employment disadvantages. One of the best used methods for model and simulation to forecast is the mathematical applications as artificial neural networks. This kind of method offers the possibility to enhance, understand and forecast the evolutions and influences between different data values. The objective of this paper is to find the proper artificial neural network for modeling and simulating of female employment evolution, under the influence of different indices. The structure considered the best for the simulated values was using hyperbolic tan function and quasi-Newton solver. Also, the ANN structures provide an average feature importance of 51.62% for Total investment, 19.95% for GDP, 15.06% for GERD and 13.37% for Production values.

Keywords

• female employment
• data model
• artificial neural network (ann)