A Framework for Semi-Automated Generation of a Virtual Combine Harvester

Author:

Hermann D.,Bilde M.L.,Andersen N.A.,Ravn O.

Publisher

Elsevier BV

Subject

Control and Systems Engineering

Reference13 articles.

1. A genetic input selection methodology for identification of the cleaning process on a combine harvester, part i: Selection of relevant input variables for identification of the sieve losses;Craessaerts;Biosystems Engineering, Biosyst. Eng, Biosyst Eng, Biosystems Eng,2007

2. A genetic input selection methodology for identification of the cleaning process on a combine harvester, part ii: Selection of relevant input variables for identification of material other than grain (mog) content in the grain bin;Craessaerts;Biosystems Engineering,2007

3. Identification of the cleaning process on combine harvesters. Part I: A fuzzy model for prediction of the material other than grain (MOG) content in the grain bin;Craessaerts;Biosystems Engineering,2008

4. Identification of the cleaning process on combine harvesters, Part II: A fuzzy model for prediction of the sieve losses;Craessaerts;Biosystems Engineering,2010

5. Eggerl, A., Bsch, H., Bruns, A., and Wbcke, S. (2010). Model-based development of control algorithms for optimizing combine prococess.

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4. The Comparative Assessment Results of Winter Soft Wheat Grain Damage During Combine Harvesting;XV International Scientific Conference “INTERAGROMASH 2022”;2023

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