Artificial neural networks as routine for error correction with an application in Singapore regional model

作者：Sun Yabin^*; Babovic Vladan; Chan Eng Soon

来源：Ocean Dynamics, 2012, 62(5): 661-669.

DOI：10.1007/s10236-012-0524-x

• Artificial neural networks
• Error correction
• Singapore regional model

This research presents an error correction scheme based on artificial neural networks, and demonstrates its application on water level forecast for the Singapore water. The error correction scheme combines the numerical model outputs with the in situ measurements on a two-step basis: (1) predicting the model errors at the measurement stations and (2) distributing the predicted errors to the nonmeasurement stations. Artificial neural networks are used in both error prediction and error distribution as the mapping function approximators. The efficiency of this scheme is tested on six water level stations in the Singapore regional model domain with four prediction horizons. The results show that this error correction scheme produces high-precision forecasts, and improves the forecast accuracy at both measurement and nonmeasurement stations.

• 出版日期2012-5