The motivation for this paper is to introduce a hybrid neural network architecture of Particle
Swarm Optimization and Adaptive Radial Basis Function (ARBF–PSO), a time varying …

An artificial neural network has been proved to be a sufficient tool for modelling fatigue life of
multidirectional composite laminates made of GFRP composite materials and tested under …

The use of neural networks trained by a new hybrid algorithm is employed on forecasting
the Greek Foreign Exchange-Rate Market. Four major currencies, namely the US Dollar (USD), …

Genetic programming is used in this paper for modeling the fatigue life of several fiber–reinforced
composite material systems. It is shown that if the genetic programming tool is …

The purpose of this article is to present a novel genetic programming trading technique in
the task of forecasting the next day returns when trading the EUR/USD exchange rate based …

An artificial neural network has proven to be a sufficient tool for modelling fatigue life of
multidirectional composite laminates made of Glass Fibre Reinforced Plastic (GFRP) composite …

In the current paper is presented the application of a Gene Expression Programming
Environment in modeling the fatigue behavior of composite materials. The environment was …

In this work MagnetoEncephaloGram (MEG) recordings of epileptic patients were analyzed
using a hybrid neural networks training algorithm. This algorithm combines genetic …

The present work deals with the optimization of resource management in communications
centers, with the aid of neural networks. Starting with a set of definitions, essential for the …

Novel computational methods such as artificial neural networks, adaptive neuro-fuzzy
inference systems and genetic programming are used in this chapter for the modeling of the …