Neurofuzzy approaches for predicting financial time series are investigated and shown to perform well in the context of various trading strategies involving stocks and options. The horizon of prediction is typically a few days and trading strategies are examined using historical data. Two methodologies are presented wherein neural predictors are used to anticipate the general behavior of financ...

A neuro-fuzzy system has been developed to model the behaviour of a fast ferry. The sources of the available knowledge are the physical laws of the vertical dynamics of the craft, and some experimental and simulated data of the ship performance in regular waves. The non-linear model has been obtained by applying adaptive neurofuzzy inference. It is focus on the vertical motion of the craft, bot...

A new approximation to the dynamics of neocortex, preserving essential functions but not the microstructure, is presented. Local feature spaces are used to replace neurodynamics of neural cell assemblies in categorization, approximation and generalization processes. A global workspace (mind space), resulting from cooperation among local feature spaces, facilitates memory-based reasoning. Implem...

This chapter describes the intersection of two areas of artificial intelligence research, genetic algorithms and neural networks. The chapter has six main sections. The first describes the motivation for this research, which is followed by a gentle introduction to the basic principles of genetic algorithms. The third section deals with the application of genetic algorithms to conventional neura...