Conventional controller’s usually required a prior knowledge of mathematical modelling of the process. The inaccuracy of mathematical modelling degrades the performance of the process, especially for non-linear and complex control problem. The process used is Water-Bath system, which is most widely used and nonlinear to some extent. For Water-Bath system, it is necessary to attain desired tempe...

There has been a growing interest in combining both neural network and fuzzy system, and as a result, neuro-fuzzy computing techniques have been evolved. ANFIS (adaptive network-based fuzzy inference system) model combined the neural network adaptive capabilities and the fuzzy logic qualitative approach. In this paper, a novel structure of unsupervised ANFIS is presented to solve differential e...

The application of neuro-fuzzy inference system to predict the compressive strengths of concrete is presented in this study. To investigate the influence of various parameters which affect the compressive strength, 2000 data samples were used for the analysis. Adaptive neuro-fuzzy inference system (ANFIS) was introduced for training and testing the data obtained from technical literatures. To r...

Weather prediction is an ever challenging area of investigation for scientists. The Adaptive Neuro-Fuzzy Inference System (ANFIS) has been widely used for modeling different kinds of nonlinear systems including rainfall forecasting. Adaptive Neuro-Fuzzy Inference Systems (ANFIS) combines the capabilities of Artificial Neural Networks (ANN) and Fuzzy Inference Systems (FIS) to solve different ki...

In this study, an efficient method is introduced to predict the stability of soil-structure interaction (SSI) system subject to earthquake loads. In the procedure of the nonlinear dynamic analysis, a number of structures collapse and then lose their stability. The prediction of failure probability is considered as stability criterion. In order to achieve this purpose, a modified adaptive neuro ...

A supervisory Adaptive Network‐based Fuzzy Inference System (SANFIS) is proposed for the empirical control of a mobile robot. This controller includes an ANFIS controller and a supervisory controller. The ANFIS controller is off‐line tuned by an adaptive fuzzy inference system, the supervisory controller is designed to compensate for the approximation error bet...

Navigation and obstacle avoidance in an unknown environment is proposed in this paper using hybrid neural network with fuzzy logic controller. The overall system is termed as Adaptive Neuro Fuzzy Inference System (ANFIS). ANFIS combines the benefits of fuzzy logic and neural networks for the purpose of achieving robotic navigation task. Simulation results are presented using Khepera Simulator (...

The paper proposed the adaptive noise suppression technique for suppression of noise in voice communication. There are different techniques earlier used for adaptive filteration like least mean square, kalman’s filter etc.In the paper we used “fuzzy logic” technique for adaptive filteration. We know about the theory of adptive filteration of noise and application of fuzzy logic. We are using th...

in this study, several data-driven techniques including system identification, adaptive neuro-fuzzy inference system (anfis), artificial neural network (ann) and wavelet-artificial neural network (wavelet-ann) models were applied to model rainfall-runoff (rr) relationship. for this purpose, the daily stream flow time series of hydrometric station of hajighoshan on gorgan river and the daily rai...

The paper introduces various methods for classification like fuzzy logic, and its combination with artificial neural networks. Datasets from UCI Repository have been used for the implementation of classification models using Matlab 7.0 for Fuzzy Inference System(FIS) and Anfis and Matlab R2007b for Anfis with variable labels and different membership functions.