Application of Soft Computing Tools for Wave Prediction at Specific Locations in the Arabian Sea Using Moored Buoy Observations

J. Vimala, G. Latha, R. Venkatesan
{"title":"Application of Soft Computing Tools for Wave Prediction at Specific Locations in the Arabian Sea Using Moored Buoy Observations","authors":"J. Vimala, G. Latha, R. Venkatesan","doi":"10.1260/1759-3131.3.4.255","DOIUrl":null,"url":null,"abstract":"The knowledge of design and operational values of significant wave heights is perhaps the single most important input needed in ocean engineering studies. Conventionally such information is obtained using classical statistical analysis and stochastic methods. As the causative variables are innumerable and underlying physics is too complicated, the results obtained from the numerical models may not always be very satisfactory. Soft computing tools like Artificial Neural Network (ANN) and Adaptive Network based Fuzzy Inference System (ANFIS) may therefore be useful to predict significant wave heights in some situations. The study is aimed at forecasting of significant wave height values in real time over a period of 24hrs at certain locations in Indian seas using the models of ANN and ANFIS. The data for the work were collected by National Institute of Ocean Technology, Chennai. It was found that the predictions of wave heights can be done by both methods with equal efficiency and satisfaction.","PeriodicalId":105024,"journal":{"name":"The International Journal of Ocean and Climate Systems","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The International Journal of Ocean and Climate Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1260/1759-3131.3.4.255","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

Abstract

The knowledge of design and operational values of significant wave heights is perhaps the single most important input needed in ocean engineering studies. Conventionally such information is obtained using classical statistical analysis and stochastic methods. As the causative variables are innumerable and underlying physics is too complicated, the results obtained from the numerical models may not always be very satisfactory. Soft computing tools like Artificial Neural Network (ANN) and Adaptive Network based Fuzzy Inference System (ANFIS) may therefore be useful to predict significant wave heights in some situations. The study is aimed at forecasting of significant wave height values in real time over a period of 24hrs at certain locations in Indian seas using the models of ANN and ANFIS. The data for the work were collected by National Institute of Ocean Technology, Chennai. It was found that the predictions of wave heights can be done by both methods with equal efficiency and satisfaction.
软计算工具在阿拉伯海特定地点用系泊浮标观测预测海浪的应用
在海洋工程研究中,重要浪高的设计和操作价值的知识可能是最重要的输入。传统上,这些信息是通过经典的统计分析和随机方法获得的。由于成因变量多、基础物理复杂,数值模型得到的结果不一定令人满意。因此,软计算工具,如人工神经网络(ANN)和基于自适应网络的模糊推理系统(ANFIS),在某些情况下可能有助于预测重要的波浪高度。本研究的目的是利用人工神经网络和ANFIS模式,实时预报印度洋某些地点24小时内的重要波高值。这项工作的数据是由金奈国家海洋技术研究所收集的。结果表明,两种方法对波浪高的预测都能达到同样的效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信