Many applications reported in artificial neural networks are associated with military
problems. This paper reviews concepts associated with the processing of military data to find …

Feature selection plays an important role in classifying systems such as neural networks
(NNs). We use a set of attributes which are relevant, irrelevant or redundant and from the …

We present a neural network based approach for identifying salient features for classification
in feedforward neural networks. Our approach involves neural network training with an …

In the last five years, many new learning algorithms have been designed and developed to
train neural networks for solving complex problems in a wide variety of domains. One of the …

This valuable text addresses different pattern recognition (PR) tasks in a unified framework
with both theoretical and experimental results. Tasks covered include data condensation …

Mass appraisal is the systematic appraisal of groups of properties as of a given date using
standardized procedures and statistical testing. Mass appraisal is commonly used to …

A major attack can significantly reduce the capability to deliver services in large-scale
networked information systems. In this project, we have addressed the survivability of large …

The observed features of a given phenomenon are not all equally informative: some may be
noisy, others correlated or irrelevant. The purpose of feature selection is to select a set of …

An experimental study on two decision issues for wrapper feature selection (FS) with
multilayer perceptrons and the sequential backward selection (SBS) procedure is presented …

In this paper a new scheme of feature ranking and hence feature selection using a Multilayer
Perception (MLP) Network has been proposed. The novelty of the proposed MLP-based …