In recent years, soft computing methods, like fuzzy logic and neural networks have been  presented and developed for the purpose of mobile robot trajectory tracking. In this paper we will present a fuzzy approach to the problem of mobile robot path tracking for the CEDRA rescue robot with a complicated kinematical model. After designing the fuzzy tracking controller, the membership functions an...

Experiments involving handwritten word recognition on words taken from images of handwritten address blocks from the United States Postal Service mailstream are described. The word recognition algorithm relies on the use of neural networks at the character level. The neural networks were trained using crisp and fuzzy desired outputs. The fuzzy outputs were defined using a fuzzy k-nearest neighb...

abstract nowadays, due to the environmental uncertainty and rapid development of new technologies, economic variables are often predicted by using less data and short-term timeframes. therefore, prediction methods which require fewer amounts of data are needed. auto regressive integrated moving average (arima) model and artificial neural networks (anns) need large amounts of data to achieve acc...

In this paper, we introduce a novel fuzzy method which is combined fuzzy relation, interaction probability values and hub structure to detect sub-communities in complex networks. We apply our method on yeast proteinprotein interaction network to identify the protein complexes. Compared with traditional method, more protein complexes have been identified by this new fuzzy method. Meanwhile, we e...

This paper presents a fuzzy system that recognizes learning styles and emotions using two different neural networks. The first neural network (a Kohonen neural network) recognizes the student cognitive style. The second neural network (a back-propagation neural network) was used to recognize the student emotion. Both neural networks are being part of a fuzzy system used into an intelligent tuto...

The goal of this expository paper is to bring forth the basic current elements of soft computing (fuzzy logic, neural networks, genetic algorithms and genetic programming) and the current applications in intelligent control. Fuzzy sets and fuzzy logic and their applications to control systems have been documented. Other elements of soft computing, such as neural networks and genetic algorithms,...

We define fuzzy constraint networks and prove a theorem about their relationship to fuzzy logic. Then we introduce Khayyam, a fuzzy constraint-based programming language in which any sentence in the first-order fuzzy predicate calculus is a well-formed constraint statement. Finally, using Khayyam to address an equipment selection application, we illustrate the expressive power of fuzzy constrai...

We define fuzzy constraint networks and prove a theorem about their relationship to fuzzy logic. Then we introduce Khayyam, a fuzzy constraint-based programming language in which any sentence in the first-order fuzzy predicate calculus is a well-formed constraint statement. Finally, using Khayyam to address an equipment selection application, we illustrate the expressive power of fuzzy constrai...