We are developing technology for generating English textual summaries of time-series data, in three domains: weather forecasts, gas-turbine sensor readings, and hospital intensive...
Somayajulu Sripada, Ehud Reiter, Jim Hunter, Jin Y...
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...
Motivated by a broad range of potential applications, we address the quantile prediction problem of real-valued time series. We present a sequential quantile forecasting model bas...
Since perceptual and motor processes in the brain are the result of interactions between neurons, layers and areas, a lot of attention has been directed towards the development of...
Abstract-- In this paper, we address the issue of forecasting for periodically measured nonstationary traffic based on statistical time series modeling. Often with time series base...