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

S.N. Londhe

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

机译：实时估算缺失波高的软计算方法

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This paper presents soft computing approach for estimation of missing wave heights at a particular location on a real-time basis using wave heights at other locations. Six such buoy networks are developed in Eastern Gulf of Mexico using soft computing techniques of Artificial Neural Networks (ANN) and Genetic Programming (GP). Wave heights at five stations are used to estimate wave height at the sixth station. Though ANN is now an established tool in time 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 well in terms of accuracy of estimation as evident from values of various statistical parameters employed. The GP models work better in case of extreme events. Results of both approaches are also compared with the performance of large-scale continuous wave modeling/forecasting system WAVEWATCH III. The models are also applied on real time basis for 3 months in the year 2007. A software is developed using evolved GP codes (C++) as back end with Visual Basic as the Front End tool for real-time application of wave estimation model.

机译：本文提出了一种软计算方法，可以使用其他位置的波高实时估算特定位置的丢失波高。利用人工神经网络（ANN）和遗传编程（GP）的软计算技术，在墨西哥东部海湾开发了六个这样的浮标网络。五个站的波高用于估计第六个站的波高。尽管现在人工神经网络已经成为时间序列分析的既定工具，但是在时间序列预测/分析领域，尤其是在海洋工程领域中，GP的使用相对较新，需要进一步探索。从所采用的各种统计参数的值可以明显看出，ANN和GP方法在估计的准确性方面均表现良好。 GP模型在发生极端事件时效果更好。还将两种方法的结果与大型连续波建模/预测系统WAVEWATCH III的性能进行了比较。该模型还于2007年在3个月内实时应用。开发了一种软件，该软件使用演进的GP代码（C ++）作为后端，并以Visual Basic作为前端工具来实时应用波浪估计模型。

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来源
《Ocean Engineering》 |2008年第12期|p.1080-1089|共10页
作者
S.N. Londhe;
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作者单位

Department of Civil Engineering, Vishwakarma Institute of Information Technology, Survey No. 2/3/4, Kondhwa (Bk), Pune 411048, Maharashtra, India;

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原文格式 PDF
正文语种 eng
中图分类海洋学;
关键词
water waves; buoy systems; soft computing; artificial neural network; genetic programming; missing data;

机译：水浪浮标系统软计算人工神经网络遗传规划数据丢失;

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1. Reply to 'Discussion of 'Soft computing approach for real-time estimation of missing wave heights' by S.N. Londhe [Ocean Engineering 35 (2008) 1080-1089]' [J] . Shreenivas N. Londhe Ocean Engineering . 2010,第13期

机译：S.N.回复“讨论'用于实时估算缺失波高的软计算方法'”。隆德[海洋工程35（2008）1080-1089]
2. Discussion on 'Soft computing approach for real-time estimation of missing wave heights' by S.N. Londhe [Ocean Engineering 35 (2008) 1080-1089] [J] . A.H. Alavi, A.H. Gandomi, A.A.R. Heshmati Ocean Engineering . 2010,第13期

机译：S.N.讨论了“实时估算缺失波高的软计算方法”。隆德[海洋工程35（2008）1080-1089]
3. A comparative study for estimation of wave height using traditional and hybrid soft-computing methods [J] . Roy Chandrabhushan, Motamedi Shervin, Hashim Roslan, Environmental earth sciences . 2016,第7期

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4. EFFECT OF MISSING LARGE WAVE DATA ON ESTIMATION ACCURACY OF RETURN WAVE HEIGHTS [C] . Hajime Mase, Toshikazu Kitano 28th International Conference on Coastal Engineering 2002: Solving Coastal Conundrums Vol.1 Jul 7-12, 2002 Cardiff, Wales . 2002

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

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