An artificial neural networks approach to product cost estimation. The case study for electric motor

• Authors: Zbigniew Leszczyński , Tomasz Jasiński
• Languages of publication: EN

Abstracts

EN

The aim of this paper is to present, in theoretical and application terms, artificial neural networks (ANNs) as a method of estimating the product cost. The first part of the article reviews the methods used to estimate the product cost. The basic approaches to the problem of product cost estimation, presented by various authors, were described. In the second part an empirical study using artificial neural networks was conducted. Two research methods were used in this paper: literature analysis and empirical research carried out in the form of an extensive case study. The test object is a new generation induction motor. The main research problem of the article is the modelling of artificial neural networks for the estimation process of product costs with advanced production technology. The test procedures focus on the application aspects. The conclusions discuss the usefulness and advantages of using ANN models in estimating the costs of products

Keywords

EN

cost estimation model; artifical neural networks; product cost

• Publisher: Wydawnictwo Uniwersytetu Ekonomicznego we Wrocławiu
• Journal: Informatyka Ekonomiczna
• Year: 2018
• Issue: 1(47)
• Pages: 72-84

Contributors

author

Zbigniew Leszczyński

author

Tomasz Jasiński