analytic programming; neural network; pattern recognition; evolution

In this paper we develop two methods that are able to analyze and recognize patterns in time series. The first model is based on analytic programming (AP). The second one uses an artificial neural network that is adapted by backpropagation. This paper also includes experimental results of time series pattern recognition carried out with both mentioned methods, which have proven their suitability for this type of problem solving.