Użyteczność modeli parametrycznych i sztucznych sieci neuronowych w prognozowaniu kosztów produkcji

Abstract

Użyteczność modeli parametrycznych i sztucznych sieci neuronowych w prognozowaniu kosztów produkcji The aim of the paper is to analyze parametric models and artificial neural networks in terms of their suitability as estimation tools of the production costs. Estimated production costs are a fundamental determinant of the decision-making process by costs engineers relating to design and management costs of new products, infrastructure projects and production lines. The first part of the paper presents a con- ceptual framework for the construction of a model of production costs parametric estimation, multidimensional with linear and nonlinear dependency. It then discusses the nature and use of artificial neural networks as nonparametric estimates of production costs. In both parts of the article, an empirical study is conducted with the use of adequate statistical methods and artificial neurons. This study presents proce- dures for construction of models of parametric and nonparametric estimation of production costs and discusses their advantages and disadvantages. It also presents the application and usefulness of both models for estimating production costs in production environment.

Keywords

• model of cost estimation
• parametric estimation
• artificial neural neurons
• estimated costs