“MODELLING OF COMPLEX CHAOTIC SIGNALS USING ARTIFICIAINTELLIGENCE”

In this project we are considering different Chaotic signals and their results so that we can work on the best method. Here Chaos (Irregular motions ) are used. Filtering has been invoked to reduce the obviously noisy character of the monthly sunspot numbers. However, here shown that straight for wardlinear filtering can also make a stochastic signal appear to below-dimensional, so one cannot eliminate the possibility that the sunspot numbers are the result of a stochastic process with a “noisily periodic” component. We are comparing numerational knowledge based techniques for forecasting has been proved highly successful in present time. The purpose of this paper is to examine the effects of several important neural network factors on model fitting and forecasting the behaviors.