neural network is one of the most widely used algorithms in the field of machine learning, on the other hand, neural network training is a complicated and important process. supervised learning needs to be organized to reach the goal as soon as possible. a supervised learning algorithm analyzes the training data and produces an inferred function, which can be used for mapping new examples.  hen...

land cover map is important for many urban planning and management activities. in this study, in order to produce land cover map of arak city, digital image of liss-iii scanner acquired on 16 june 2006 were employed. first of all, geometric correction with rmse 0.58 pixel was applied. considering the mountainous condition of the study area, topographic correction was applied to the image. in su...

Cox regression model serves as a statistical method for analyzing the survival data, which requires some options such as hazard proportionality. In recent decades, artificial neural network model has been increasingly applied to predict survival data. This research was conducted to compare Cox regression and artificial neural network models in prediction of kidney transplant survival. The prese...

Cox regression model serves as a statistical method for analyzing the survival data, which requires some options such as hazard proportionality. In recent decades, artificial neural network model has been increasingly applied to predict survival data. This research was conducted to compare Cox regression and artificial neural network models in prediction of kidney transplant survival. The prese...

A novel speech separation structure which simulates the cocktail party e ect using a modi ed iterative Wiener lter and a multi-layer perceptron neural network is presented. The neural network is used as a speaker recognition system to control the iterative Wiener lter. The neural network is a modi ed perceptron with a hidden layer using feature data extracted from LPC cepstral analysis. The pro...

This paper presents an investigation into classifying myoelectric signals using a new fuzzy clustering neural network architecture for control of multifunction prostheses. Moreover, a comparative study of the classification accuracy of myoelectric signals using multi-layer perceptron with back-propagation algorithm, and the new fuzzy clustering neural network (FCNN) is presented. The myoelectri...

introduction: with using multiple linear regression (mlr), can simultaneously analyses several different variables, but to get the desirable results from the mlr, the samples must be much and accurate. therefore, this method has high sensitivity and may cause errors in results. in addition, to use this method, the variable must have normal distribution and modification follow from a linear rela...