A growing concern for organisations is how they should deal with increasing amounts of collected data. With fierce competition and smaller margins, organisations that are able to fully realize the potential in the data they collect can gain an advantage over the competitors. It is almost impossible to avoid imprecision when processing large amounts of data. Still, many of the available informat...

A novel technique to classify time series with imprecise hidden Markov models is presented. The learning of these models is achieved by coupling the EM algorithm with the imprecise Dirichlet model. In the stationarity limit, each model corresponds to an imprecise mixture of Gaussian densities, this reducing the problem to the classification of static, imprecise-probabilistic, information. Two c...

in the paper a model to predict the concentrations of particulate matter pm10, pm2.5, so2, no, co and o3 for a chosen number of hours forward is proposed. the method requires historical data for a large number of points in time, particularly weather forecast data, actual weather data and pollution data. the idea is that by matching forecast data with similar forecast data in the historical data...