artificial neural networks have the advantages such as learning, adaptation, fault-tolerance, parallelism and generalization. this paper mainly intends to offer a novel method for finding a solution of a fuzzy equation that supposedly has a real solution. for this scope, we applied an architecture of fuzzy neural networks such that the corresponding connection weights are real numbers. the sugg...

the aim of this study is quantity determining and evaluating of the quality position of teaching and learningprocess. so, the artificial neural networks were used for modeling nonlinear relationships to inspect and evaluate different models of service quality evaluation. the statistical population include 1070 peoples, which were master and phd students of faculty of agriculture of ferdowsiuniv...

This paper focuses on a new kind of artificial neural networks – the Z-transform artificial neural networks (ZTANN). It is proposed to use the Z-transform instead of ordinary weights and a linear activation function of an artificial neuron. This extension allows to use artificial neural networks in new areas. The ordinary description of artificial neural networks is a special case of the descri...

Since the early 1990s, artificial neural networks play an increasing role in the development of new biomedical systems. In United States, over last decades, the granted biomedical patents that explicitly refer to artificial neural networks in their title, abstract or key references amount to about 50% of the total number of granted biomedical patents with a significant element of computational ...

Artificial neural networks have the advantages such as learning, adaptation, fault-tolerance, parallelism and generalization. This paper mainly intends to offer a novel method for finding a solution of a fuzzy equation that supposedly has a real solution. For this scope, we applied an architecture of fuzzy neural networks such that the corresponding connection weights are real numbers. The ...

In their seminal paper [1] McCulloch and Pitts have shown the strong relationship between finite automata and so-called McCullochPitts networks. Our goal is to extend this result to weighted automata. In other words, we want to integrate artificial neural networks and weighted automata. For this task, we introduce semiring artificial neural networks, that is, artificial neural networks which im...

DOWNLOAD http://bit.ly/1OslRBc Artificial neural networks: theory and applications This comprehensive tutorial on artifical neural networks covers all the important neural network architectures as well as the most recent theory-e.g., pattern recognition, statistical theory, and other mathematical prerequisites. A broad range of applications is provided for each of the architectures. Artificial ...