Corpus ID: 17561422

Data Mining Approach for Predictive Modeling of Agricultural Yield Data

@inproceedings{Marinkovi2009DataMA,
  title={Data Mining Approach for Predictive Modeling of Agricultural Yield Data},
  author={Branko Marinkovi and J. Crnobarac and Sanja Brdar and B. Anti and Vladimir Crnojevi},
  year={2009}
}
  • Branko Marinkovi, J. Crnobarac, +2 authors Vladimir Crnojevi
  • Published 2009
  • Prediction of agricultural yields is a challenging task that demands fusion of knowledge from different areas such as data mining, statistics and agriculture. This paper shows that data mining techniques can be successfully applied to agricultural data analysis. Results that we present are gained on the data set that contains monthly measurements of different environmental parameters and annual yields for maize, soybean and sugar beet. Obtained results are in compliance with previous results on… CONTINUE READING

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