<abstract xmlns="http://www.w3.org/1999/xhtml"><p>Comparative analyses in the national scale were carried out in 300 individual farms from Małopolskie and Świętokrzyskie Voivodeship in order to search for relations between the production intensity level, work performance and land efficiency and factors which shape them. The analyses concerned the use of Bayesian modelling algorithms for forecasting development of various economic and agricultural indicators which decide on the intensity and competitiveness of agriculture. The paper constitutes the second stage of research, which was preceded with previous preparation of data for modelling with the use of an exploratory overview of available data and TwoStep Cluster Analysis (<xref ref-type="bibr" rid="j_agriceng-2017-0017_ref_007_w2aab2b8c17b1b7b1ab1ab7Aa">Grotkiewicz et al., 2016</xref>). Based on the analyses, which were carried out, networks were built which present the relations between the analyzed variables, and conditional similarities were verified.</p></abstract>

Comparative analyses in the national scale were carried out in 300 individual farms from Małopolskie and Świętokrzyskie Voivodeship in order to search for relations between the production intensity level, work performance and land efficiency and factors which shape them. The analyses concerned the use of Bayesian modelling algorithms for forecasting development of various economic and agricultural indicators which decide on the intensity and competitiveness of agriculture. The paper constitutes the second stage of research, which was preceded with previous preparation of data for modelling with the use of an exploratory overview of available data and TwoStep Cluster Analysis (Grotkiewicz et al., 2016). Based on the analyses, which were carried out, networks were built which present the relations between the analyzed variables, and conditional similarities were verified.

Application of Bayesian Networks for Forecasting Future Model of Farm

Institute of Agricultural Engineering and Informatics

Agricultural Engineering

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"Application of Bayesian Networks for Forecasting Future Model of Farm"}

Comparative analyses in the national scale were carried out in 300 individual farms from Małopolskie and Świętokrzyskie Voivodeship in order to search for...

Application of Bayesian Networks for Forecasting Future Model of Farm

Online veröffentlicht: 26. Juni 2017

Seitenbereich: 69 - 79

Eingereicht: 01. Nov. 2016

Akzeptiert: 01. Jan. 2017

DOI: https://doi.org/10.1515/agriceng-2017-0017

Schlüsselwörter
Bayesian Networks, forecasting, economic and agricultural indicators, farm

© 2017 Katarzyna Grotkiewicz, published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Application of Bayesian Networks for Forecasting Future Model of Farm

Online veröffentlicht: 26. Juni 2017

Seitenbereich: 69 - 79

Eingereicht: 01. Nov. 2016

Akzeptiert: 01. Jan. 2017

DOI: https://doi.org/10.1515/agriceng-2017-0017

SchlüsselwörterBayesian Networks, forecasting, economic and agricultural indicators, farm

© 2017 Katarzyna Grotkiewicz, published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Schlüsselwörter
Bayesian Networks, forecasting, economic and agricultural indicators, farm