Search Results for author:
Found 2 papers, 0 papers with code
PBRE: A Rule Extraction Method from Trained Neural Networks Designed for Smart Home Services
We also apply PBRE to extract rules from a smart home service represented by an NRL (Neural Network-based Reinforcement Learning).
Observation Error Covariance Specification in Dynamical Systems for Data assimilation using Recurrent Neural Networks
In this work, we propose a data-driven approach based on long short term memory (LSTM) recurrent neural networks (RNN) to improve both the accuracy and the efficiency of observation covariance specification in data assimilation for dynamical systems.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
