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Integration of artificial neural networks
into an lindenmayer system based plant
modeling environment with mathematica
Based on the output of the artificial neural networks, method of the artificial neural networks. In order to
it can be derived the growth parameter. It is then applied visualize the plant, the virtual growth of Zinnia Elegane
to the plant, in such a way that it is possible to get the crop
th
Jacq with the 5 treatment (75% inorganic and organic
as expected. Once the stalk growth is obtained, then the fertilizer is 100%) is shown in figure 7.
leaf and bloom growth need to be found using the similar
Fig. 8 Growth processes of Zinnia Elegane Jacq plant of Iteration 7
CONCLUSION
REFERENCES
This research shows that the Integration of the Lindenmayer, P. Prusinkiewicz. The Algorithmic Beauty
artificial neural networks into L-system based Plant of Plants, Springer Verlag, New York, pp. 227,
modeling Environment has been implemented. In this 1990.
research, it can be demonstrated that the difference Jacob, C., Genetic L-System Programming: Breeding and
between the artificial neural networks output and the
Evolving Artificial Flowers with Mathematica,
actual plant growth is less than 6% on average. It is
First Int. Mathematica Symposium, Southampton,
concluded from this research that the agriculture of Zinnia UK, Computational Mechanics Pub, 1995
Elegane Jacq plant could be develop further with the R. Mech, P. Prusinkiewicz. Visual Models of Plants
artificial neural networks, which both controlled
Interacting with Their Environment, Proceedings
environment and controlled mixture of fertilizer are used of SIGGRAPH 96, ACM SIGGRAPH, p. 397,
as decision support system. 1996.
Studia Universitatis “Vasile Goldiş”, Seria Ştiinţele Vieţii
Vol. 22, issue 3, 2012, pp. 411-418
© 2012 Vasile Goldis University Press (www.studiauniversitatis.ro)
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