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dc.contributor.authorTrajer, Jędrzej
dc.contributor.authorPietrzycka, Iwona
dc.contributor.authorPiotrowska, Ewa
dc.contributor.authorGolisz, Ewa
dc.date.accessioned2018-03-02T11:39:41Z
dc.date.available2018-03-02T11:39:41Z
dc.date.issued2017-11
dc.identifier.citationTrajer J., Pietrzycka I., Piotrowska E., Golisz E. 2017. Apple Tree Yield Analysis Using Data Mining. [in:] Lorencowicz E. (ed.), Uziak J. (ed.), Huyghebaert B. (ed.). Farm Machinery and Processes Management in Sustainable Agriculture, 9th International Scientific Symposium. ULS Lublin, p.384-388en
dc.identifier.isbn978-83-937433-2-2
dc.identifier.otherDOI: 10.24326/fmpmsa.2017.69
dc.identifier.urihttps://depot.ceon.pl/handle/123456789/14766
dc.description.abstractThe paper analyses an orcharding farm that specializes in apple trees production. Based on the data for the period of 2008-2014, the authors analysed the main factors that might have impact on apple yield. A computer system for assessment of apple trees cultivation efficiency that aids in making appropriate decisions allowing for obtaining the highest yield, was proposed. The system was developed using selected Data Mining techniques such as cluster analysis and Kohonen networks. The system may be useful for decision support in sustainable horticulture production, and thus contributes to the development of sustainable agriculture. Although its quality is acceptable it still requires improvement using a bigger dataset.en
dc.language.isoen
dc.publisherDepartment of Machinery Exploitation and Management of Production Processes, University of Life Sciences in Lublin, Polanden
dc.rightsUznanie autorstwa-Użycie niekomercyjne 3.0 Polska*
dc.rights.urihttp://creativecommons.org/licenses/by-nc/3.0/pl/*
dc.subjectapple tree yieldingen
dc.subjectdata miningen
dc.subjectsustainable gardening productionen
dc.titleApple Tree Yield Analysis Using Data Miningen
dc.typearticleen
dc.typeconferenceObjecten
dc.contributor.organizationFaculty of Production Engineering, Warsaw University of Life Sciences – SGGWen


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