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

• Type: Journal
• Year: 2008
• Where: ENVSOFT
• Authors: Ralf Wieland, Wilfried Mirschel
• Keywords: ENVSOFT 2008, Neural Network, Radial Basis Function, Radial Basis Function Network