Breast cancer diagnosis has been approached by various machine learning techniques for many years. This paper presents a study on classification of Breast cancer using Feed Forward Artificial Neural Networks. Back propagation algorithm is used to train this network. The performance of the network is evaluated using Wisconsin breast cancer data set for various training algorithms. The highest ac...

We use simulated soccer to study multi-agent learning. Each team member tries to learn from the corresponding human player in a real game. Following a uniied approach, strategic and tactical behavior is learned synergistically by training a feed-forward neural network (ANN) with a mod-iied back-propagation algorithm. It aims at decreasing the learning time and avoiding the local maximums. We tr...

A comparative study of artificial neural network (ANN) and multiple regression is made to predict the fat tail weight of Balouchi sheep from birth, weaning and finishing weights. A multilayer feed forward network with back propagation of error learning mechanism was used to predict the sheep body weight. The data (69 records) were randomly divided into two subsets. The first subset is the train...

Facial expression recognition is also gaining interest among the researchers because of its inevitable advantages in image retrieval which can be extended many fields like medicine, artificial intelligence, robotics and neural networks. So it is one of the hot topic for researchers. Existing methods such as PCA, LDA, LPP etc. with Euclidian distance classifier are popular. Neural network classi...

We proposed a method for improving the performance of the back propagation algorithm by introducing the adaptive gain of the activation function. In a ‘feed forward’ algorithm, the slope of the activation function is directly influenced by a parameter referred to as ‘gain’. In this paper, the influence of the adaptive gain on the learning ability of a neural network is analysed. Multi layer fee...

-This paper focuses the function approximation capability of feed forward neural network (FFNN). A Graphical user Interface (GUI) system has been developed and tested for function approximation. This GUI system can approximate any nonlinear/linear function which can have any number of input variable and six output variables. Configuration of neural network can be set from a single GUI window. A...

Development of medical domain application has been one of the most active research areas. Neural Networks are one of many data mining analytical tools that can be utilized to make predictions for medical data. Model selection for a neural network includes various factors such as selection of the optimal number of hidden nodes, selection of the relevant input variables and selection of optimal c...

This paper demonstrates classification of PQ events utilizing wavelet transform (WT) energy features by artificial neural network (ANN) and SVM classifiers. The proposed scheme utilizes wavelet based feature extraction to be used for the artificial neural networks in the classification. Six different PQ events are considered in this study. Three types of neural network classifiers such as feed ...