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ENVSOFT
2008

Adaptive fuzzy modeling versus artificial neural networks

8 years 9 months ago
Adaptive fuzzy modeling versus artificial neural networks
In this paper two areas of soft computing (fuzzy modeling and artificial neural networks) are discussed. Based on the fundamental mathematical similarity of fuzzy technique and radial basis function networks a new training algorithm for fuzzy models was introduced. A feed forward neural network (NN), a radial basis function network (RBF) and a trained fuzzy algorithm are compared for regional yield estimation of agricultural crops (winter rye, winter barley). As training pattern a data set from a training region (Maerkisch-Oderland district, Germany) and as test pattern a data set from a three times larger region were used. Specific advantages and disadvantages of these methods for the estimation of yield were discussed. Key words: Fuzzy modeling; artificial neural network; feed forward network; radial basis function network; training algorithm; yield estimation; agricultural crops
Ralf Wieland, Wilfried Mirschel
Added 10 Dec 2010
Updated 10 Dec 2010
Type Journal
Year 2008
Where ENVSOFT
Authors Ralf Wieland, Wilfried Mirschel
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