Abstract This research deals with the use of self-organising maps for the classification of text documents. The aim was to classify documents to separate classes according to their...
A new evolutionary algorithm, Elitistic Evolution (termed EEv), is proposed in this paper. EEv is an evolutionary method for numerical optimization with adaptive behavior. EEv uses...
The problem we address in this paper is that of finding effective and parsimonious patterns of connectivity in sparse associative memories. This problem must be addressed in real n...
Weiliang Chen, Reinoud Maex, Rod Adams, Volker Ste...
Many complex, real world phenomena are difficult to study directly using controlled experiments. Instead, the use of computer simulations has become commonplace as a feasible alte...
Ivo Couckuyt, Dirk Gorissen, Hamed Rouhani, Eric L...
Modern process and condition monitoring systems produce a huge amount of data which is hard to analyze manually. Previous analyzing techniques disregard time information and concen...
Abstract. The Levenstein or edit distance was developed as a metric for calculating distances between character strings. We are looking at weighting the different edit operations (...
In this paper we present our original methodology, in which Matching Pursuit is used for networks anomaly and intrusion detection. The architecture of anomaly-based IDS based on si...
Lukasz Saganowski, Michal Choras, Rafal Renk, Wito...
We propose a generalized model with configurable discretizer actuators as a solution to the problem of the discretization of massive numerical datasets. Our solution is based on a ...
A statistical generative model is presented as an alternative to negative selection in anomaly detection of string data. We extend the probabilistic approach to binary classificat...
In this paper we present application of genetic programming (GP) [1] to evolution of indirect encoding of neural network weights. We compare usage of original HyperNEAT algorithm w...