Conference Dates
May 13-17, 2007
Abstract
The dynamic behavior of fluidized bed has been studied based on the chaos theory. The experiments were done in a fluidized bed of 0.15 m diameter using an optical fiber probe. The interval between successive clusters in the fluidized bed were calculated from the time series signals and proved to be chaotic by calculating the correlation dimension. An artificial neural network (ANN) was adapted and trained to predict the generated time series. The ANN results were compared with the predictions of the k-Nearest Neighbor (kNN) method to show the superiority of ANN in chaotic time series prediction.
Recommended Citation
Shayan Karimipour, Navid Mostoufi, and Rahmat Sotudeh -Gharebagh, "Prediction of the Dynamics of a Fluidized Bed Reactor using Artificial Neural Networks" in "The 12th International Conference on Fluidization - New Horizons in Fluidization Engineering", Franco Berruti, The University of Western Ontario, London, Canada; Xiaotao (Tony) Bi, The University of British Columbia, Vancouver, Canada; Todd Pugsley, University of Saskatchewan, Saskatoon, Saskatchewan, Canada Eds, ECI Symposium Series, (2007). https://dc.engconfintl.org/fluidization_xii/88