Author(s): Vectors Of Flow Field; Wulonghua
Linked Author(s):
Keywords: Multi-evidence reasoning; Hopfield neural networks; Identification miss-vector; Flow field
Abstract: In the course of the measurement velocity field, because of measurement error, there are inevitably miss-vectors in the original flow field which is measured. The neural network has been an important means for its characteristic to identify miss-vector. In this paper, based on simulating the identification process of cerebra to miss-vector; a new Hopfield neural network model of multi-evidence reasoning is founded. And the identification performance of this model is tested by numerical simulation experiment. The experiment result indicates that, compared with other network model of single-evidence reasoning, the new network model of multi-evidence reasoning can simulate cerebra ideation better, it has better identification function.
Year: 2007