English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

In technical systems understood in terms of Agile Systems, the important elements are information flows between all phases of an object existence. Among these information streams computation processes play an important role and can be done automatically and also in a natural way should include consideration of uncertainty. This article presents a model of such a process implemented in a Bayesian network technology. The model allows the prediction of the unit costs of operation of a combine harvester based on the monitoring of dependent variables. The values of the decision variables representing the parameters of the machine’s operation and the intensity and the conditions for its operation, are known to an accuracy, which is defined by a probability distribution. The study shows, using inference mechanisms built into the network, how cost simulation studies of various situational options can be carried out.

Implementation of computation process in a bayesian network on the example of unit operating costs determination