A novel recurrent neurofuzzy network is proposed in this paper. More specifically, in this work we generalize the recurrent neurofuzzy network structure proposed in [1], which is in turn is an improvement of the feedforward structure introduced in [2]. The network structure is composed by two structures: a fuzzy inference system and a neural network. The fuzzy inference system contains fuzzy ne...

With the development of critical loads, power quality problem has become particularly important and poor power quality will be cause many adverse effects and the cost of many deaths will follow. To improve power quality and protection of sensitive loads against grid disturbances have been used new equipment based on power electronics similar FACTs devices, they are Custom Power. One of the most...

Improving the efficiency of dynamic routing problem on road network is a difficult .There is numerous works proposed for this problem and they try to solve this in different aspects. Most of the existing routing problem based on static approach. In this paper, we propose a fuzzy Dijkstra’s shortest path algorithm based on dynamic approach. The linguistic variables that qualify user parameters a...

Fuzzy approach and artificial neural networks become effective tool for researchers by forecasting fuzzy time series. The relation of these has advantage to improve forecasting performance especially in handling nonlinear systems. Hence, in this study we aimed to handle a nonlinear problem to apply neural network-based fuzzy time series model. Differing from previous studies, we used various de...

In this paper, the author research on electrical equipment’s fault diagnosis based on the improved support vector machine and fuzzy clustering. Combining the support vector combined fuzzy sets and neural network to carry on the fault diagnosis is a most prosperous diagnosis method. This article put forward a sample processing method using fuzzy clustering and studied the application of fuzzy co...

In this paper, we intend to offer a new method based on fuzzy neural networks for finding a real solution of fuzzy equations system. Our proposed fuzzified neural network is a fivelayer feed-back neural network that corresponding connection weights to output layer are fuzzy numbers. The proposed architecture of artificial neural network, can get a real input vector and calculates it’s correspon...

This paper deals with the design of single fuzzy neural network (SFNN) with sliding mode control (SMC) systems by using the approach of sliding mode control. The fuzzy sliding mode control (FSMC) in the system guarantee the state can reach the user-defined surface in finite time and then it slides into the origin along the surface. The key idea is to apply parameters of the membership function ...

A shortest path problem is a practical issue in networks for real-world situations. This paper addresses the fuzzy shortest path (FSP) problem to obtain the best fuzzy path among fuzzy paths sets. For this purpose, a new efficient algorithm is introduced based on a new definition of ideal fuzzy sets (IFSs) in order to determine the fuzzy shortest path. Moreover, this algorithm is developed for ...

Dealing with uncertainty is one of the most critical problems in complicatedpattern recognition subjects. In this paper, we modify the structure of a useful UnsupervisedFuzzy Neural Network (UFNN) of Kwan and Cai, and compose a new FNN with 6 types offuzzy neurons and its associated self organizing supervised learning algorithm. Thisimproved five-layer feed forward Supervised Fuzzy Neural Netwo...

This chapter shows a new method of fuzzy network which can change the structure by the systems. This method is based on the self-organizing mapping (SOM) (Kohonen T. 1982), but this algorithm resolves the problem of the SOM which can’t change the number of the network nodes. Then, this new algorithm can change the number of fuzzy rules; it takes the experienced rules out of the necessary side f...