Neural Network World; International Journal on Neural and Mass - Parallel Computing and Information Systems

Training All the Kdd Data Set to Classify and Detect Attacks

The purpose of this study is to analyze the performances of some neural networks (NNs) when all the KDD data set is used to train them, in order to classify and detect attacks. Five different types of NNs were tested: Multi-Layer Perceptron (MLP), Self Organization Feature Map (SOFM), Radial Basis Function/Generalized Regression/Probabilistic (RBF/GR/P), Jordan/Elman, and Recurrent NNs. The experiment study is done on the Knowledge Discovery and Data mining (KDD) data sets. We consider two le...

Quantitative Trading of Gold and Silver Using Nonlinear Models

The main aim of this paper is to forecast gold and silver daily returns with advanced regression analysis using various linear and non-linear models. ARMA models are used as a linear benchmark for comparison purposes with established non-linear models such as Nearest Neighbours and MultiLayer Perceptron (MLP), and Higher Order Neural Networks (HONN) whose application to financial markets is quite new. All models are assessed using statistical criteria such as correct directional change as wel...

Multispectral Image Classification Using Modified K-Means Algorithm

Clustering is used to organize data for efficient retrieval. A popular technique for clustering is based on k-Means such that the data is partitioned into k clusters. In k-Means clustering a set of n data points in d-dimensional space R^sup d^, an integer k is given and the problem is to determine a set of k-points in R^sup d^ called centers, to minimize the mean squared distance from each point to its nearest center. In this method, the number of clusters is predefined and the technique is h...

Bees Algorithm for Null Synthesizing of Linear Antenna Arrays by Controlling Only the Element Positions

This paper presents bees algorithm (BA) for null steering of linear an- tenna arrays by controlling only the element positions. The BA is an optimization algorithm inspired by the natural foraging behavior of honey bees to find the op- timal solution. To show the versatility and flexibility of the proposed BA, several examples of Chebyshev array pattern with the imposed single, multiple and broad nulls are given. It is found that the nulling technique based on BA is capable of steering the ar...