Adaptivity to non-stationary contexts is a very important property for intelligent systems in general, as well as to a variety of applications of knowledge based systems in the area of Electric Power Systems. In this paper we present an innovative Neural-Fuzzy architecture that exhibits three important properties: online adaptation, knowledge (rule) modeling, and knowledge extraction from numer...

Motion control of mobile robots is a typical nonlinear tracking control issue and has been discussed with different control schemes such as PID, GPC, sliding mode, predictive control etc[1]-[3]. Intelligent control techniques, based on neural networks and fuzzy logic, have also been developed for path tracking control of mobile robots[4][5]. While conventional neural networks have good ability ...

suitable soil structure is important for crop growth. one of the main characteristics of soil structure is the size of soil aggregates. there are several ways of showing the stability of soil aggregates, among which the determination of the median weight diameter of soil aggregates is the most common method. in this paper, a method based on adaptive neuro fuzzy inference system (anfis) was used...

in common classical methods of cavity depth estimation through microgravity data, usually when a pre-geometrical model is considered for the cavity shape, the simple geometrical models of sphere, vertical cylinder and horizontal cylinder are commonly used. it is obviously an important fact that in real conditions the shapes of the cavities are not exactly sphere, horizontal cylinder or vertical...

This paper introduces the application of Adaptive Neuro-Fuzzy Inference System (ANFIS) for fault classification in transmission lines. It will be addressed clearly in this paper. The ANFIS can be viewed either as a fuzzy system, a neural network or fuzzy neural network (|FNN). This paper is integrating the learning capabilities of neural network to the robustness of fuzzy logic systems in the s...

The Gustafson-Kessel fuzzy clustering algorithm is capable of detecting hyperellipsoidal clusters of different sizes and orientations by adjusting the covariance matrix of data, thus overcoming the drawbacks of conventional fuzzy c-means algorithm. In this paper, an adaptive version of the Gustafson-Kessel algorithm is proposed. The way to adjust the covariance matrix iteratively is introduced ...

this study investigates the oil extraction from pistacia khinjuk by the application of enzyme.artificial neural network (ann) and adaptive neuro fuzzy inference system (anfis) were applied formodeling and prediction of oil extraction yield. 16 data points were collected and the ann was trained with onehidden layer using various numbers of neurons. a two-layered ann provides the best results, us...

implementation of enterprise resource planning has had a chaotic history in which many projects ended successfully and many failed or ended without approaching the predetermined objectives. this research, in terms of purpose, is considered fundamental since it designs a new system for solving a fundamental problem and it is also an applied research because the research result is deployed in the...

This paper explores a multi-modular architecture of an intelligent information system and proposes a method for adaptation in it. The method is based on evaluating which of the modules need to be adapted based on the performance of the whole system on new data. These modules are then trained selectively on the new data until they improve their performance and the performance of the whole system...