Optimization of neural network topology, weights and neuron transfer functions for given data set and problem is not an easy task. In this article, we focus primarily on building optimal feed-forward neural network classifier for i.i.d. data sets. We apply meta-learning principles to the neural network structure and function optimization. We show that diversity promotion, ensembling, self-organ...

This paper investigates the ability of several alternate models of Artificial Neural Network (ANN) to predict the probability of occurrence of Hypertension (HT) in a mixed patient population. To do this a two-layer feed-forward neural network with 13 inputs and 1 output was created with a single hidden layer . Different types of networks structures, such as NEWFF (feed-forward back propagation ...

Aiming at the characteristics which variable air volume air conditioning system is multi-variable, nonlinear and uncertain system, normal fuzzy neural network is hard to meet the requirements which dynamic control of multi-variable. In this paper, we put forward a recursive neural network predictive control strategy based on wavelet neural network model. Through recursive wavelet neural network...

In this paper is presented an investigation of the speech recognition classification performance. This investigation on the speech recognition classification performance is performed using two standard neural networks structures as the classifier. The utilized standard neural network types include Feed-forward Neural Network (NN) with back propagation algorithm and a Radial Basis Functions Neur...

The main objective of this project is cell nuclei segmentation and classification. In pre-processing convert the gray scale and apply the segmentation. In segmentation this project proposes the graph cut algorithm. After segmentation the features are extracts such as texture and etc. In classification this project used the feed forward neural network. The proposed method is very efficient. The ...

Neural networks are a powerful tool used to model properties and behaviour of materials in many areas of civil engineering applications. In the present paper, the models in artificial neural networks for predicting the temperatures in timber under fire loading have been developed. For building these models, training and testing using the available numerical results obtained using design methods...

drought forecasting in khash city by using neural network model hossein negaresh associate professor of geography and environmental planningfaculty, university of sistan & baluchestan mohsen armesh holding master degree in climatology in environmental planning extended abstract 1- introduction drought is condition of lack of rainfall and increase in temperature occurring in any climatic condit...

Facial expression recognition has attracted much attention in recent years because of its importance in realizing highly intelligent human-machine interfaces. In this paper, we propose a new facial expression recognition technique that utilizes the 2-D DCT of full size facial images and eigenvectors based feed forward neural network. The neural network is designated to separate group of facial ...