Development of a regional neural network for coastal water level predictions

Huang, Wenrui; Murray, Catherine; Kraus, Nicholas C.; Rosati, Julie Dean

doi:10.1016/s0029-8018(03)00083-0

Cited by 80 publications

(29 citation statements)

References 11 publications

(11 reference statements)

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“…Since the principle of ANN has been well documented in the literature, only a brief explanation is given in this section. The feasibility of three-layer for the reproduction of complex system behaviour was proved empirically by a number of applications (Huang et al 2003, Lee 2004, Makarynskyy et al 2004, Pierini and Gómez 2009.…”

Section: The Artificial Neural Networkmentioning

confidence: 99%

Investigating prediction performance of an artificial neural network and a numerical model of the tidal signal at Puerto Belgrano, Bahia Blanca Estuary (Argentina)

et al. 2013

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A b s t r a c tIn the present study we compare performances of the prediction of hourly tidal level variations at Puerto Belgrano, a coastal site in the Bahia Blanca Estuary (Argentina), by means of the MOHID model, which is a numerical model designed for coastal and estuarine shallow water applications, and of an artificial neural network (ANN). It was shown that the ANN model is able to predict the hourly tidal levels over long term duration with at least seven days of observations and with a better performance in respect to the numerical model. Our findings can be useful to implement ANN-based tools for future studies of the hydrodynamics of Bahía Blanca estuary.

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Section: The Artificial Neural Networkmentioning

confidence: 99%

Investigating prediction performance of an artificial neural network and a numerical model of the tidal signal at Puerto Belgrano, Bahia Blanca Estuary (Argentina)

et al. 2013

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“…Typical applications in problems related to water flows could be seen in The ASCE Task Committee (2000). Some of the recent studies involving wave analysis and forecasting are given in Deo and Naidu (1999), Krasnopolsky et al (2002), Huang et al (2003), DelBalzo et al (2003), Makarynskyy (2004), Tolman et al (2004), Altunkaynak and Ozger (2004), Makarynskyy et al (2005) and Lee (2006).…”

Section: The Networkmentioning

confidence: 99%

Derivation of coastal wind and wave parameters from offshore measurements of TOPEX satellite using ANN

Kalra

Deo

2007

Coastal Engineering

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“…Other tools are models based on artificial intelligence (AI), which are less burdensome than the numerical models, avoid uncertainties arising from physical modelling and are very useful for predicting and understanding the coastal response to changes produced by climatic agents (waves, currents, tides, winds, and so on). So these tools have been used successfully in predicting wave (Kalra et al, 2005;Lee, 2008), coastal water level (Ghorbani et al, 2010;Huang et al, 2003;Lee et al, 2007;Makarynska and Makarynskyy, 2008), wind-wave analysis (Browne et al, 2007;Herman et al, 2009), plant geometry bay beaches (Iglesias et al, 2009), and so on. Finally, tools such as SVM can be applied.…”

Section: Introductionmentioning

confidence: 99%