This paper describes a new framework for using natural selection to evolve Bayesian Networks for use in forecasting time series data. It extends current research by introducing a ...
Forecasting workflow activity durations is of great importance to support satisfactory QoS in workflow systems. Traditionally, a workflow system is often designed to facilitate the...
Abstract. Accurate and fine-grained prediction of future user location and geographical profile has interesting and promising applications including targeted content service, adv...
This paper demonstrates the feasibility and potential of applying empirical mode decomposition (EMD) to forecast the arrival time behaviors in a parallel batch system. An analysis...
Abstract. Local air quality forecasting can be made on the basis of meteorological and air pollution time series. Such data contain redundant information. Partial mutual informatio...