优化DHT-RBF模型替代ARMA-RBF模型用于风电预测

S. Mukhopadhyay, P. K. Panigrahi, A. Mitra, P. Bhattacharya, M. Sarkar, P. Das
{"title":"优化DHT-RBF模型替代ARMA-RBF模型用于风电预测","authors":"S. Mukhopadhyay, P. K. Panigrahi, A. Mitra, P. Bhattacharya, M. Sarkar, P. Das","doi":"10.1109/ICE-CCN.2013.6528534","DOIUrl":null,"url":null,"abstract":"ARMA-Neural model is an established useful model for the Wind Power forecasting purpose. In the current work we introduced Discrete Hilbert Transform (DHT)-Neural Model which provides better result than the ARMA-Neural Model. We know that a signal and its' DHT produces the same Energy Spectrum. Based on this concept in this paper DHT is used for Wind Speed forecasting purpose. Thereafter the RBF neural network is used on this to forecast wind power. Taking the data of measured wind speed from Weather Forecasting Bureau Report as example, we validate the method described above.","PeriodicalId":286830,"journal":{"name":"2013 IEEE International Conference ON Emerging Trends in Computing, Communication and Nanotechnology (ICECCN)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"Optimized DHT-RBF model as replacement of ARMA-RBF model for wind power forecasting\",\"authors\":\"S. Mukhopadhyay, P. K. Panigrahi, A. Mitra, P. Bhattacharya, M. Sarkar, P. Das\",\"doi\":\"10.1109/ICE-CCN.2013.6528534\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ARMA-Neural model is an established useful model for the Wind Power forecasting purpose. In the current work we introduced Discrete Hilbert Transform (DHT)-Neural Model which provides better result than the ARMA-Neural Model. We know that a signal and its' DHT produces the same Energy Spectrum. Based on this concept in this paper DHT is used for Wind Speed forecasting purpose. Thereafter the RBF neural network is used on this to forecast wind power. Taking the data of measured wind speed from Weather Forecasting Bureau Report as example, we validate the method described above.\",\"PeriodicalId\":286830,\"journal\":{\"name\":\"2013 IEEE International Conference ON Emerging Trends in Computing, Communication and Nanotechnology (ICECCN)\",\"volume\":\"51 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-03-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 IEEE International Conference ON Emerging Trends in Computing, Communication and Nanotechnology (ICECCN)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICE-CCN.2013.6528534\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE International Conference ON Emerging Trends in Computing, Communication and Nanotechnology (ICECCN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICE-CCN.2013.6528534","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 11

摘要

arma -神经网络模型是一种成熟的风力发电预测模型。本文介绍了离散希尔伯特变换(DHT)-神经模型,该模型比arma -神经模型具有更好的结果。我们知道一个信号和它的DHT产生相同的能谱。基于这一概念,本文将DHT用于风速预报。在此基础上,利用RBF神经网络对风电进行预测。以气象局报告中的实测风速数据为例,对上述方法进行了验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimized DHT-RBF model as replacement of ARMA-RBF model for wind power forecasting
ARMA-Neural model is an established useful model for the Wind Power forecasting purpose. In the current work we introduced Discrete Hilbert Transform (DHT)-Neural Model which provides better result than the ARMA-Neural Model. We know that a signal and its' DHT produces the same Energy Spectrum. Based on this concept in this paper DHT is used for Wind Speed forecasting purpose. Thereafter the RBF neural network is used on this to forecast wind power. Taking the data of measured wind speed from Weather Forecasting Bureau Report as example, we validate the method described above.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
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