this paper is concerned with the development of a novel classifier for automatic mass detection of mammograms, based on contourlet feature extraction in conjunction with statistical and fuzzy classifiers. in this method, mammograms are segmented into regions of interest (roi) in order to extract features including geometrical and contourlet coefficients. the extracted features benefit from...

this paper intends to offer a new iterative method based on articial neural networks for finding solution of a fuzzy equations system. our proposed fuzzied neural network is a ve-layer feedback neural network that corresponding connection weights to output layer are fuzzy numbers. this architecture of articial neural networks, can get a real input vector and calculates its corresponding fu...

porosity is one of the fundamental petrophysical properties that should be evaluated for hydrocarbon bearing reservoirs. it is a vital factor in precise understanding of reservoir quality in a hydrocarbon field. log data are exceedingly crucial information in petroleum industries, for many of hydrocarbon parameters are obtained by virtue of petrophysical data. there are three main petrophysical...

This paper intends to offer a new iterative method based on articial neural networks for finding solution of a fuzzy equations system. Our proposed fuzzied neural network is a ve-layer feedback neural network that corresponding connection weights to output layer are fuzzy numbers. This architecture of articial neural networks, can get a real input vector and calculates its corresponding fuzzy o...

In this paper, the author research on electrical equipment’s fault diagnosis based on the improved support vector machine and fuzzy clustering. Combining the support vector combined fuzzy sets and neural network to carry on the fault diagnosis is a most prosperous diagnosis method. This article put forward a sample processing method using fuzzy clustering and studied the application of fuzzy co...

This paper is concerned with the development of a novel classifier for automatic mass detection of mammograms, based on contourlet feature extraction in conjunction with statistical and fuzzy classifiers. In this method, mammograms are segmented into regions of interest (ROI) in order to extract features including geometrical and contourlet coefficients. The extracted features benefit from...

This paper consists of a survey of various engineering, computational biology, medicine, etc applications based on the fuzzy neural network model, and also a summary of the recent techniques such as still support vector machine, self-organizing map, principal component analysis. The advantage of the fuzzy neural network is that it is closer to biophysical reality and mathematically more tractab...