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Most of the real life classification problems have ill defined, imprecise or fuzzy class boundaries. Feedforward neural networks with conventional backpropagation learning algorithm are not tailored to this kind of classification problem. Hence, in this paper, feedforward neural networks, that use backpropagation learning algorithm with fuzzy objective functions, are investigated. A learning al...

In this paper are presented results obtained in a vowel recognition task applying fuzzy neural networks. The vowels, uttered from 10 speakers each in 1000 different contexts are recognized using as features the first three formant frequencies. The results obtained in this case show that fuzzyfication process improves the recognition rate of the classical variants. The paper is organized in 6 ch...

In recent years, the use of hybrid soft computing methods has shown that in various applications the synergism of several techniques is superior to a single technique. For example, the use of a neural fuzzy system and an evolutionary fuzzy system hybridises the approximate reasoning mechanism of fuzzy systems with the learning capabilities of neural networks and evolutionary algorithms. Evoluti...

the functions employed in an estimation of costly measured soil properties from either widely available or more easily obtained basic soil properties are referred to as pedotransfer functions. to develop pedotransfer functions, one can use multivariate regression, neural networks and neuro-fuzzy models. to make a comparison among the mentioned models, 153 soil samples were collected from soils ...

A novel fuzzy-neural tree (FNT) is presented, where each tree node uses a Gaussian as a fuzzy membership or possibility distribution in place of sigmoidal function in conventional neural networks. Although neural networks with Gaussian activation functions as well as different types of cooperative neuro-fuzzy systems have been extensively described in the literature, the FNT presented in this p...

Neural networks and fuzzy systems have been the subject of much interest in recent years for the control of nonlinear processes. Much research has been directed at indirect control schemes where, basically, the neural network or fuzzy system has been used to identify the process, and a controller has been synthesised from this model. An alternative approach is that of direct control where the n...