In this article the eVectiveness of some recently developed genetic algorithm-based pattern classiŽ ers was investigated in the domain of satellite imagery which usually have complex and overlapping class boundaries. Landsat data, SPOT image and IRS image are considered as input. The superiority of these classiŽ ers over k-NN rule, Bayes’ maximum likelihood classiŽ er and multilayer perceptron ...

One essential task in information extraction from the medical corpus is drug name recognition. Compared with text sources come from other domains, the medical text is special and has unique characteristics. In addition, the medical text mining poses more challenges, e.g., more unstructured text, the fast growing of new terms addition, a wide range of name variation for the same drug. The mining...

A new class of Neural Networks (NN), designated the Multiple Feed-Forward (MFF) networks, and a new gradient-based learning algorithm, Multiple Back-Propagation (MBP), are proposed and analyzed. MFF are obtained by integrating two feed-forward networks (a main network and a space network) in a novel manner. A major characteristic is their ability to partition the input space by using selective ...

Diabetes is a condition in which the amount of sugar in the blood is higher than normal. Classification systems have been widely used in medical domain to explore patient’s data and extract a predictive model or set of rules. The prime objective of this research work is to facilitate a better diagnosis (classification) of diabetes disease. There are already several methodology which have been i...

This paper presents a critical study about the use of some neural networks (NNs) to detect and classify intrusions. The aim of our research is to determine which NN classifies well the attacks and leads to the higher detection rate of each attack. This study focused on two classification types of records: a single class (normal, or attack), and a multiclass, where the category of attack is also...

In the last few years a lot of research has been carried out in the field of deliverance of information for improving its efficiency and reliability. However, the systematic analysis and verification of channel performance triggered wide interest of new researchers. The popular technique for transmission of signals over wireless channels was orthogonal frequency division multiplexing (OFDM). In...

To simulate the broiler growth the input variables were: day of year, vents opening, wind velocity, external temperature and absolute humidity, the maximum, average and minimum of the internal temperature and absolute humidity. For that purpose, two techniques were applied, a multi-layer perceptron (MLP) static Neural Network (NN) and the Layered Digital Dynamic Network (LDDN) which were applie...

Finger vein is one of the most fitting biometric for identifying individuals. In this paper a new method for finger vein recognition is proposed. First the veins are extracted from finger vein images by using entropy based thresholding. In finger vein images the veins are appeared as dark lines. The method extracts veins as well, but the images are noisy, that means in addition to the veins the...

Abstract Anomalous diffusion behavior can be observed in many single-particle (contained crowded environments) tracking experimental data. Numerous models used to describe such In this paper, we focus on two common processes: fractional Brownian motion (fBm) and scaled (sBm). We proposed novel methods for sBm anomalous parameter estimation based the autocovariance function (ACVF). Such a functi...

Stock market prediction is forever important issue for investor. Computer science plays vital role to solve this problem. From the evolution of machine learning, people from this area are busy to solve this problem effectively. Many different techniques are used to build predicting system. This research describes different state of the art techniques used for stock forecasting and compare them ...