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Data Mining with Neural Networks for Wheat Yield Prediction

  • Georg Ruß
  • Rudolf Kruse
  • Martin Schneider
  • Peter Wagner
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5077)

Abstract

Precision agriculture (PA) and information technology (IT) are closely interwoven. The former usually refers to the application of nowadays’ technology to agriculture. Due to the use of sensors and GPS technology, in today’s agriculture many data are collected. Making use of those data via IT often leads to dramatic improvements in efficiency. For this purpose, the challenge is to change these raw data into useful information. In this paper we deal with neural networks and their usage in mining these data. Our particular focus is whether neural networks can be used for predicting wheat yield from cheaply-available in-season data. Once this prediction is possible, the industrial application is quite straightforward: use data mining with neural networks for, e.g., optimizing fertilizer usage, in economic or environmental terms.

Keywords

Precision Agriculture Data Mining Neural Networks Prediction 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Georg Ruß
    • 1
  • Rudolf Kruse
    • 1
  • Martin Schneider
    • 2
  • Peter Wagner
    • 2
  1. 1.Otto-von-Guericke-University of Magdeburg 
  2. 2.Martin-Luther-University of Halle 

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