Many fuzzy time series approaches have been proposed in recent years. These methods include three main phases such as fuzzification, defining fuzzy relationships and, defuzzification. Aladag et al. [2] improved the forecasting accuracy by utilizing feed forward neural networks to determine fuzzy relationships in high order fuzzy time series. Another study for increasing forecasting accuracy was...

The paper presents the possibility of the design of frontal neural networks and feed-forward neural networks (without pre-processing of inputs time series) with learning algorithms on the basis genetic and eugenic algorithms and Takagi-Sugeno fuzzy inference system (with pre-processing of inputs time series) in predicting of gross domestic product development by designing a prediction models wh...

A system that segments and labels tabla strokes from real performances is described. Performance is evaluated on a large database taken from three performers under different recording conditions, containing a total of 16,834 strokes. The current work extends previous work by Gillet and Richard (2003) on categorizing tabla strokes, by using a larger, more diverse database that includes their dat...

Feature extraction methods and subsequent neural network performances are explored in this paper. Object recognition method ‘regionprops’ and moment invariants are used to extract basic characteristics from acquired bloodstain images. The extracted features are in return fed into a neural network for the purpose of pattern recognition. The blood drop in the image is first detected using sobel e...

Monitoring system for induction motor is widely developed to detect the incipient fault. Such system is desirable to detect the fault at the running condition to avoid the motor stop running suddenly. In this paper, a new method for detection system is proposed that emphasizes the fault occurrences as temporary short circuit in induction motor winding. The investigation of fault detection is fo...

In this study, an artificial neural network was used to predict the minimum force required to single point incremental forming (SPIF) of thin sheets of Aluminium AA3003-O and calamine brass Cu67Zn33 alloy. Accordingly, the parameters for processing, i.e., step depth, the feed rate of the tool, spindle speed, wall angle, thickness of metal sheets and type of material were selected as input and t...

Automated grading system plays an important role in many industries. In ceramic industries, the grading of ceramic tiles is a difficult task as it has huge variations of surface properties. In this paper, automated surface grading system based on Discrete Wavelet Transform (DWT) and Gray Level Co-occurrence Matrices (GLCM) is presented. Texture information’s in ceramic tiles are effectively rep...

This paper presents two innovative evolutionary-neural systems based on feed-forward and recurrent neural networks used for quantitative analysis. These systems have been applied for approximation of phenol concentration. Their performance was compared against the conventional methods of artificial intelligence (artificial neural networks, fuzzy logic and genetic algorithms). The proposed syste...

One of the major problems faced by the oilfields in the middle time is casing damage. The neural network, the improvement BP as well as the three-layer feed forward neural network applied in damage diagnosis is a key way to prevent damage. The formations of the damage are corresponded to the input vector. Factors such as casing age limit, strata stress, soaking time are described as real Number...

This document describes the architecture of neuro fuzzy systems. First part of the document provides a review of general notions of fuzzy logic, and structure of fuzzy systems. A procedure and different types of fuzzy reasoning are described. The second part is devoted to the neural networks and to the simplest model of artificial neuron. In the third part, the similarities and differences betw...