PROCEEDINGS IPMU '08
Optimizing Wheat Yield Prediction Using Different Topologies of Neural Networks
G. Russ, R. Kruse, M. Schneider, P. Wagner
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 by using decision rules.
These rules include the management
know-how for (economic) optimal
recommendations. This paper deals
with suitable modeling techniques
for those agricultural data where the
objective is to uncover the existing
patterns. In consequence, yield prediction
is enabled based on cheaply
available site data. Based on this
prediction, economic or environmental
optimization of, e.g., fertilization
can be carried out.
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