Two independent evolutionary modeling methods, based on fuzzy logic and neural networks respectively, are applied to predicting trend reversals in financial time series, and their...
This paper describes a model for generating time series which exhibit the statistical phenomenon known as long-range dependence (LRD). A Markov Modulated Process based upon an inf...
We study the problem of providing a sensor with an accurate estimate of the time, from a novel perspective which is complementary to the well-studied clock synchronization problem....
In this study, a hybrid intelligent data mining methodology, genetic algorithm based support vector machine (GASVM) model, is proposed to explore stock market tendency. In this hyb...
Knowledge Discovery in time series usually requires symbolic time series. Many discretization methods that convert numeric time series to symbolic time series ignore the temporal ...