Soft computing approach for real-time estimation of missing wave heights

This paper presents soft computing approach for estimation ( f missing wave heights at a particular location on a real-time basis using wave heights at other I)cations. Six such buoy networks are developed in Eastern Gulf of Mexico using soft computing tE :hniques of Artificial Neural Networks (ANN) and Genetic Programming (GP). Wave heights at five stat Dns are used to estimate wave height at tile sixth station. Though ANN is now an established tool in timi series analysis, use of GP in the field of time series forecasting/analysis particularly in the area of Ocean Engineering is relatively new and needs to be explored further. Both ANN and GP approach perform wE 11 in terms of accuracy of estimation as evident from values of various statistical parameters employec, The GP models work better in case of extreme events. Results of both approaches are also compar( d with the performance of large-scale continuous wave model i ng/forecasti ng system WAVEWATCH 1 1. The models are also applied on real time basis for 3 months in the year 2007. A software is develop d using evolved CP codes (C++) as back end with Visual Basic as the Front End tool for real-time appli, ation of wave estimation model.(c) 2008 Elsevier Ltd. All rights reserved.