Soft and hard computing approaches for real-time prediction of currents in a tide-dominated coastal area

Abstract

The prediction of tidal currents in the coastal region on a real-time or online basis is useful in taking operation-and planning-related decisions such as towing of vessels and monitoring of oil slick movements. Currently, however, this is done in offline mode on the basis of the statistical method of harmonic analysis involving fitting of harmonic functions to measured data. Alternatively, numerical solutions of hydrodynamic models can also provide spatial and temporal information on currents. Owing to the complex real sea conditions, such methods may not always yield satisfactory results. This paper discusses a few alternative approaches based on the soft computing tools of artificial neural networks (ANNs) and genetic programming (GP), as well as the hard mathematical approaches of stochastic and statistical methods. The suggested schemes use only a univariate time series of currents to forecast their future values. The measurements of coastal currents made at two locations in the Gulf of Khambhat along the west coast of India have been analysed. The current predictions over a time step of 20 min, a few hours, and a day at the specified locations were carried out. It was found that the soft computing schemes of GP and ANN performed better than the traditional hard technique of harmonic analysis in the present application. This work should initiate more application of GP in coastal engineering. Addressing the problem of current predictions in real-time mode based on analysis of observed time series of ocean currents is a specialty of this work.

Genetic Programming: A Novel Computing Approach in Modeling Water Flows

“…In another earlier works of GP current predictions over a time step of twenty minutes, one hour, 3 hours, 6 hours, 12 hours and 24 hours at 2 locations in the tidal dominated area of the Gulf of Khambhat along west coast of India was carried out using two soft techniques of ANN and GP and 2 hard techniques of traditional harmonic analysis and ARIMA [16]. The work involved antecedent values of current only to forecast the current for various lead times at these locations.…”

‘Application of Genetic Programming for estimation of ocean wave heights’

“…Several types of ANN are found to be more accurate in comparison with these methods. Recently, researchers [5], [6], [7], [8] found GP to be a promising tool to estimation oceanic parameters.…”

A combined numerical and neural technique for short term prediction of ocean currents in the Indian Ocean

“…Alternatively an ANN can be trained using locationspecific measurements and used for forecasting, (as done in Charhate et al 2007) such an approach based entirely on data-driven schemes has not received wide acceptance from the user community who traditionally believes in the physics-based approach. We have therefore tried to combine both numerical as well as data driven techniques in this work.…”

“…An overview of ANN applications in ocean engineering in general has been given in (Jain and Deo 2006). In particular Charhate et al (2007) have shown how ANN's can effectively carry out short term current forecasting in a tide dominated bay based on real time current measurements made at a specific site. Similarly Saha et al (2015) have demonstrated how efficiently trained networks can overcome certain deficiencies of such ANN methods.…”