In this paper, the problem of time series prediction is studied. A Bayesian procedure based on Gaussian process models using a nonstationary covariance function is proposed. Exper...
Abstract. Process mining allows for the automated discovery of process models from event logs. These models provide insights and enable various types of model-based analysis. This ...
Wil M. P. van der Aalst, M. H. Schonenberg, Minseo...
This paper is concerned with the task of travel-time prediction for an arbitrary origin-destination pair on a map. Unlike most of the existing studies, which focus only on a parti...
Many emerging distributed applications require the realtime processing of large amounts of data that are being updated continuously. Distributed stream processing systems offer a ...
Nonlinear model predictive control (MPC) of a simulated chaotic cutting process is presented. The nonlinear MPC combines a neural-network model and a genetic-algorithm-based optim...