Discover and visualize association rules from sensor observations on the web
The Journal of Supercomputing
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Long-term range streamflow forecast plays an invaluable role in water resources planning andmanagement. In this study, the potential applicability and limitations of the time series forecasting approach using neural network with the multiresolution learning paradigm (NNMLP) are investigated. The predictedlongterm range streamflows using the NNMLP are compared with the observations. The results show that the time series forecasting approach of NNMLP has good predicting skill. The NNMLP requires only historicalstreamflow information. The time series forecasting approach of NNMLP has great potential for being used alone in regions with limited available information, and for being combined with other approaches to improve long-term range streamflow forecasts.