Agronomy Science, przyrodniczy lublin, czasopisma up, czasopisma uniwersytet przyrodniczy lublin

Management improvement methods in agricultural enterprises

Waldemar Bojar




Abstract

There were presented possibilities and limits of applications of Decision Support Systems (DSS) in the scope of farm machinery selection in agricultural enterprises. The proposed solutions of Artificial Intelligence class made it possible to more effectively prepare decisions of managers often using still not the most innovative manufacturing methods and not outstanding information systems. It is possible thanks to applied knowledge base acquisition and verification procedures and standardized data bases in the system named: “Method of Farm Machinery Usage Evaluation (MOWM).”

Keywords:

Decision Support Systems, optimal machinery selection, Artificial Intelligence, knowledge base

Bojar W., 2005. Studium wyboru maszyn w gospodarstwach rolniczych w świetle rozwoju systemów wspomagania decyzji. Rozprawy, 114. ATR w Bydgoszczy.
Bojar W., 2006. Unification of the data and the knowledge bases at national and the EU level being a challenge facing agriculture in the knowledge societies. [In:] The Conference Proceedings on Information Technology in Business, Warsaw Agric. Univ., Dep. of Econometrics and Computer Science.
Pawlak J., Wójcicki Z., 2004. Rola postępu technicznego w rozwoju produkcji rolniczej. Post. Nauk Roln. 3, 81–95.
Szeptycki A., Wójcicki Z., 2003. Postęp technologiczny i nakłady energetyczne w rolnictwie. IBMER Warszawa.
Wójcicki Z., 2000. Wyposażenie techniczne i nakłady materiałowo-energetyczne w rozwojowych gospodarstwach rolniczych. IBMER Warszawa.
Wójcicki Z., 2003. Modernizacja rozwojowych gospodarstw rodzinnych. Prace Nauk. AE we Wrocławiu 983, 537, 541, 543.

Published
2008-03-21



Waldemar Bojar 



License

Articles are made available under the conditions CC BY 4.0 (until 2020 under the conditions CC BY-NC-ND 4.0).
Submission of the paper implies that it has not been published previously, that it is not under consideration for publication elsewhere.

The author signs a statement of the originality of the work, the contribution of individuals, and source of funding.

 

Agronomy Science has adopted a self-archiving policy called blue by the Sherpa Romeo database. From 2021 authors can self-archive article postprints and editorial versions (under the CC BY 4.0 licence). Articles from earlier years (available under the CC BY-NC-ND 4.0 licence) can only be self-archived as editorial versions.


Most read articles by the same author(s)