This paper deals with the implementation of the Adaptive neuro fuzzy inference system (ANFIS) on a Xilinx based Field Programmable Gate Array Spartan-3E. The implemented hardware is then used to efficiently calibrate the U-Tube manometer, in which the relation between the level of mercury and the Capacitance developed across the Copper Plates of the manometer is highly non-linear. This system s...

This paper proposes the implementation of a very simple but efficient Adaptive Neuro-Fuzzy Inference System ( ANFIS )based algorithm to detect the edges of an gray scale image. The proposed approach begins by scanning the images using floating 3x3 pixel window. ANFIS system designed has 8 inputs, which corresponds to 8 pixels of instantaneous scanning matrix, one output that tells whether the p...

This paper introduces the configuration and investigation of Neuro-Fuzzy controller taking into account Adaptive Neuro-Fuzzy Inference System (ANFIS) structural engineering for Load recurrence control of a segregated wind-smaller scale hydro-diesel half and half power framework, to manage the recurrence deviation and force deviations. Because of the sudden burden changes and discontinuous wind ...

Nonlinear system identification is becoming an important tool which can be used to improve control performance. This paper describes the application of adaptive neuro-fuzzy inference system (ANFIS) model for controlling a car. The vehicle must follow a predefined path by supervised learning. Backpropagation gradient descent method was performed to train the ANFIS system. The performance of the ...

The Fusion of Artificial Neural Networks (ANN) and Fuzzy Inference System (FIS) has attracted a growing interest of researchers in various scientific and engineering areas due to the growing need for adaptive intelligent systems to solve real world problems. ANN learns by adjusting the interconnections between layers. FIS is a popular computing framework based on the concept of fuzzy set theory...

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...

The prediction of elastic modulus is one of the fundamental facts of structural engineering studies. The performance of adaptive neuro-fuzzy inference system (ANFIS) for predicting the elastic modulus of normaland high-strength concrete was investigated. Results indicate that the proposed ANFIS modeling approach outperforms the other given models in terms of prediction capability. According to ...

System modelling based on conventional mathematical tools like differential equations is not well suited for dealing with ill-defined and uncertain systems. By contrast, a fuzzy inference system, employing fuzzy if–then rules can model the qualitative aspects of human knowledge and reasoning processes without employing precise quantitative analyses. This fuzzy modeling or fuzzy identification e...

The application of the neuro-fuzzy inference system to predict the compressive strength of concrete is presented in this study. The adaptive neuro-fuzzy inference system (ANFIS) is introduced for training and testing the data sets consisting of various parameters. To investigate the influence of various parameters which affect the compressive strength, 1551 data pairs are collected from the tec...

Nonlinear system identification is becoming an important tool which can be used to improve control performance. This paper describes the application of adaptive neuro-fuzzy inference system (ANFIS) model for controlling a car. The vehicle must follow a predefined path by supervised learning. Back-propagation gradient descent method was performed to train the ANFIS system. The performance of the...