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) ...

In this paper the superheating system of a 325MW steam power generating plant is modeled by usage of recurrent neuro-fuzzy networks and subtractive clustering. The experimental data are obtained from a complete set of field experiments under various operating conditions. Neuro-fuzzy models are constructed for each subsystem of the superheating unit. The nine fuzzy models are then constructed in...

This study investigated the prediction of suspended sediment load in a gauging station in the USA by neuro-fuzzy, conjunction of wavelet analysis and neuro-fuzzy as well as conventional sediment rating curve models. In the proposed wavelet analysis and neuro-fuzzy model, observed time series of river discharge and suspended sediment load were decomposed at different scales by wavelet analysis. ...

realizing the difficulties involved in direct measurement of soil properties, in recent years, alternative methods have been employed. in the present research, soil texture, organic carbon, saturation percentage and lime as readily measurable parameters, wilting point, field capacity, cation exchange capacity as well as bulk density, as predicted variables were evaluated. the data set was then ...

Fuzzy systems, neural networks and its combination in neuro-fuzzy systems are already well established in data analysis and system control. Especially, neurofuzzy systems are well suited for the development of interactive data analysis tools, which enable the creation of rule-based knowledge from data and the introduction of a-priori knowledge into the process of data analysis. However, its rec...

Air conditioning system is developed using mamdani fuzzy model and neuro fuzzy model. It is two input one output system where inputs being the temperature and humidity measured from their respective sensors and the output being the signal that controls the compressor speed. Both the models are simulated using MATLAB Fuzzy logic Toolbox and their results are compared. Keywords— air conditioning,...

In this paper, a framework of a unified neural and neuro-fuzzy approach to integrate implicit and explicit knowledge in hybrid intelligent systems is presented. In the developed hybrid system, training data used for neural and neuro-fuzzy models represents implicit domain knowledge. On the other hand, the explicit domain knowledge is represented by fuzzy rules, directly mapped into equivalent c...

The natural development of hybrid techniques causes biases with their roots in di erent technologies, in this case either in fuzzy systems or in neural networks. The neuro-fuzzy research is discussed in this paper giving examples and emphasising the neural network perspective. Introduction of new fuzzy systems models and the development of new neural learning algorithms could be observed in the...

Proper models for prediction of time series data can be an advantage in making important decisions. In this study, we tried with the comparison between one of the most useful classic models of economic evaluation, auto-regressive integrated moving average model and one of the most useful artificial intelligence models, adaptive neuro-fuzzy inference system (ANFIS), investigate modeling procedur...

The objective of this work was to develop and to evaluate neuro-fuzzy systems as a methodology to describe coffee harvester machine operational performance when compared to multiple regression models. It was considered as input variables fruit maturation index, in the levels of 75.70, 87.00, 98.70%, operational speed, in the levels of 0.16, 0.26, 0.57m.s-1 and rods vibration, in the frequencies...