Modeling human operator’s behavior as a controller in a closed-loop control system recently finds applications in areas such as training of inexperienced operators by expert operator’s model or developing warning systems for drivers by observing the driver model parameter variations. In this research, first, an experimental setup has been developed for collecting data from human operators as th...

It is essential to have a uniform and calm flow field for a primary settling tank with high performance. In other words reducing the kinetic energy of the flow inside the settling tank can improve significantly the efficiency of these tanks and give opportunity to particles to settle in the settling zone of the tank. So determination of the velocity magnitude in various positions can be a good ...

The survey and modeling of the deformations of large structures is a major task in engineering geodesy. In this paper, a new procedure to describe and predict the deformations is presented and discussed which is based on Neuro-Fuzzy modeling. Neuro-Fuzzy methods are data driven; they deduce the model directly from the data. Hence, they are mostly convenient if there are no physical models avail...

Handwritten character recognition is an area with many applications. Over the last decade much research has gone into algorithms to develop systems, which accurately convert images of handwriting to text. At the same time, neuro-fuzzy classification models have been researched and proven to solve complex problems. In this paper, two popular models, Adaptive Neuro-Fuzzy Inference System (ANFIS) ...

A new operator for restoring digital images corrupted by impulse noise is presented. The proposed operator is a hybrid filter obtained by appropriately combining a new decision based switching median filter Canny Edge Detector and a Adaptive Neuro-Fuzzy Inference System (ANFIS). The internal parameters of the neuro-fuzzy network are adaptively optimized by training. The most distinctive feature...

In this paper discrete choice models, Logit and Probit are examined in order to predict the economic recession or expansion periods in USA. Additionally we propose an adaptive neuro-fuzzy inference system with triangular membership function. We examine the in-sample period 1947-2005 and we test the models in the out-of sample period 2006-2009. The forecasting results indicate that the Adaptive ...

this study investigates the prediction model of compressive strength of self–compacting concrete (scc) by utilizing soft computing techniques. the techniques consist of adaptive neuro–based fuzzy inference system (anfis), artificial neural network (ann) and the hybrid of particle swarm optimization with passive congregation (psopc) and anfis called psopc–anfis. their performances are comparativ...

In this work, an adaptive critic-based neuro-fuzzy is presented for an unmanned bicycle. The only information available for the critic agent is the system feedback which is interpreted as the last action the controller has performed in the previous state. The signal produced by the critic agent is used alongside the back propagation of error algorithm to tune online conclusion parts of the fuzz...

The implementation of a Neuro-Fuzzy nonlinear adaptive structure, with Local Linear Models (LLM), designed for fuel pressure estimation in diesel common-rail (CR) hydraulic system, represents the main topic. Hydraulic systems, in general, are nonlinear and engineers have often struggled to find the best solution to approximate the input-output dependencies. Powerful tools are necessary for spli...