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...

The paper focuses on the application of neuro-fuzzy techniques in fault detection and isolation. The objective of this paper is to detect and isolate faults to an industrial gas turbine, with emphasis on faults occurred in the actuator part of the gas turbine. A neuro-fuzzy based learning and adaptation of TSK fuzzy models is used for residual generation, while for residual evaluation a neuro-f...

Development of Load sensor is done in this paper, the input output of the load sensor is taken from the optical fiber sensor and the inputs are load and displacement and output is voltage. Load sensor is implemented by using two models i.e. mamdani fuzzy model and neuro fuzzy model and both the models are simulated using MATLAB, Fuzzy logic Toolbox and the results of the two models are compared...