Storm surge level prediction based on improved NARX neural network

Real-time Data Assimilation for Chaotic Storm Surge Model Using NARX Neural Network

Siek, M. and Solomatine, D.P., 2011. Real-time data assimilation for chaotic storm surge model using NARX neural network. Journal of Coastal Research, SI 64 (Proceedings of the 11th International Coastal Symposium), 1189 – 1194. Szczecin, Poland, ISSN 0749-0208 This paper introduces a real-time data assimilation technique where Nonlinear AutoRegressive with eXogenous inputs (NARX) neural networ...

Traffic Prediction Based on Improved Neural Network

Artificial neural networks and genetic algorithms derived from the corresponding simulation of biology, anatomy. The paper analyzes the advantages and the disadvantages of the artificial neural networks and genetic algorithms. The artificial neural networks and genetic algorithms to be combine in the prediction model. This method is used to predict traffic volume in a road, the accuracy of fore...

Storm Surge Prediction for Louisiana Coast Using Artificial Neural Networks

Forecast of storm surge by means of artificial neural network

This study describes the construction and verification of a model of sea level changes during a storm surge, applying artificial neural network (ANN) methodology in hydrological forecasting in a tideless sea where the variation of water level is only wind generated. Some neural networks were tested to create the forecast model. The results of ANN were compared with observed sea-level values, an...

Multi-Output Artificial Neural Network for Storm Surge Prediction in North Carolina

During hurricane seasons, emergency managers and other decision makers need accurate and ‘on-time’ information on potential storm surge impacts. Fully dynamical computer models, such as the ADCIRC tide, storm surge, and wind-wave model take several hours to complete a forecast when configured at high spatial resolution. Additionally, statically meaningful ensembles of high-resolution models (ne...