This paper presents an application of adaptive neuro-fuzzy (ANFIS) control for switched reluctance motor (SRM) speed. The ANFIS has the advantages of expert knowledge of the fuzzy inference system and the learning capability of neural networks. An adaptive neuro-fuzzy controller of the motor speed is then designed and simulated. Digital simulation results show that the designed ANFIS speed cont...

Real life data sets often suffer from missing data. The neuro-rough-fuzzy systems proposed hitherto often cannot handle such situations. The paper presents a neuro-fuzzy system for data sets with missing values. The proposed solution is a complete neuro-fuzzy system. The system creates a rough fuzzy model from presented data (both full and with missing values) and is able to elaborate the answe...

Neuro-fuzzy systems have been used for robot navigation applications because of their ability to exert human like expertise and to utilize acquired knowledge to develop autonomous navigation strategies. In this paper, neuro-fuzzy based system is proposed for reactive navigation of a mobile robot using behavior based control. The proposed algorithm uses discrete sampling based optimal training o...

0957-4174/$ see front matter 2009 Elsevier Ltd. A doi:10.1016/j.eswa.2009.02.043 * Corresponding author. Tel.: +3

This paper presents prediction of liquefaction potential of soils by neuro-fuzzy models evaluated using Idriss and Boulanger method. In order to address the collective knowledge built up in conventional liquefaction method, an alternative Takagi-Sugeno-Kang reliant neuro-fuzzy model has been developed. Neuro-fuzzy is one of the artificial intelligence approaches that can be classified by machin...

A fuzzy logic and neuro-fuzzy system for classification of hydrometeor type based on polarimetric radar measurements is described in this paper. The hydrometeor classification system is implemented by using fuzzy logic and a neural network, where the fuzzy logic is used to infer hydrometeor type, and the neural network learning algorithm is used for automatic adjustment of the parameters of the...

T. D. Dongale, T .G. Kulkarni, S.R.Jadhav, S.V.Kulkarni, R. R. Mudholkar Reserch Student, Department of Electronics, Shivaji University, Kolhapur, India, [email protected] Reserch Student, Department of Electronics, Shivaji University, Kolhapur, India, [email protected] Reserch Student, Department of Electronics, Shivaji University, Kolhapur, India, [email protected] Reserch ...

The paper presents a comparison of various soft computing techniques used for filtering and enhancing speech signals. The three major techniques that fall under soft computing are neural networks, fuzzy systems and genetic algorithms. Other hybrid techniques such as neuro-fuzzy systems are also available. In general, soft computing techniques have been experimentally observed to give far superi...