Abstract: In this brief, we investigate the approximation theory (AT) of Bayesian recurrent neural network (BRNN) for stochastic time series forecasting (TSF) from a probabilistic standpoint. Due to ...

This group project explores the use of neural networks to model avalanche hazard forecasts using a 15-year dataset from the Scottish Avalanche Information Service (SAIS). Our group has been assigned ...

Cultured neural tissues have been widely used as a simplified experimental model for brain research. However, existing devices for growing and recording neural tissues, which are manufactured using ...

In this important study, the authors model reinforcement-learning experiments using a recurrent neural network. The work examines if the detailed credit assignment necessary for back-propagation ...

Abstract: Recurrent fuzzy neural network (RFNN) are widely used with nonlinear system modeling. However, the modeling ability of RFNN is usually compromised due to the presence of uncertain external ...