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|標題:||Neural network for wave forecasting among multi-stations||作者:||Tsai, C.P.
|關鍵字:||neural network;back-propagation algorithm;wave forecasting;data;supplement||Project:||Ocean Engineering||期刊/報告no：:||Ocean Engineering, Volume 29, Issue 13, Page(s) 1683-1695.||摘要:||
Unlike in the open sea, the use of wind information for forecasting waves may encounter more ambiguous uncertainties in the coastal or harbor area due to the influence of complicated geometric configurations. Thus this paper attempts to forecast the waves based on learning the characteristics of observed waves, rather than the use of the wind information. This is reported in this paper by the application of the artificial neural network (ANN), in which the back-propagation algorithm is employed in the learning process for obtaining the desired results. This model evaluated the interconnection weights among multi-stations based on the previous short-term data, from which a time series of waves at a station can be generated for forecasting or data supplement based on using the neighbor stations data. Field data are used for testing the applicability of the ANN model. The results show that the ANN model performs well for both wave forecasting and data supplement when using a short-term observed wave data. (C) 2002 Elsevier Science Ltd. All rights reserved.
|Appears in Collections:||土木工程學系所|
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