人工神经网络在水电站入坝流量时变预测中的应用

K. Ichiyanagi, Hideo Kobayashi, T. Matsumura, Y. Kito
{"title":"人工神经网络在水电站入坝流量时变预测中的应用","authors":"K. Ichiyanagi, Hideo Kobayashi, T. Matsumura, Y. Kito","doi":"10.1109/ANN.1993.264323","DOIUrl":null,"url":null,"abstract":"This paper describes an attempt to apply a neural network method to forecast river flow rate following a fall of rain. The authors use a perceptron-type network comprised of three layers. The input data to the neural network are rainfall amounts and subsequent river flow rates. Further the predicted total volume and duration of the spell of rainfall in question are taken as additional input data. The output from the neural network is forecasted river flow rate. It is found from these investigations that the forecasting accuracy of the neural network is improved by utilization of the linear input-output relations of neurons.<<ETX>>","PeriodicalId":121897,"journal":{"name":"[1993] Proceedings of the Second International Forum on Applications of Neural Networks to Power Systems","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1993-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Application of artificial neural network to forecasting methods of time variation of the flow rate into a dam for a hydro-power plant\",\"authors\":\"K. Ichiyanagi, Hideo Kobayashi, T. Matsumura, Y. Kito\",\"doi\":\"10.1109/ANN.1993.264323\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper describes an attempt to apply a neural network method to forecast river flow rate following a fall of rain. The authors use a perceptron-type network comprised of three layers. The input data to the neural network are rainfall amounts and subsequent river flow rates. Further the predicted total volume and duration of the spell of rainfall in question are taken as additional input data. The output from the neural network is forecasted river flow rate. It is found from these investigations that the forecasting accuracy of the neural network is improved by utilization of the linear input-output relations of neurons.<<ETX>>\",\"PeriodicalId\":121897,\"journal\":{\"name\":\"[1993] Proceedings of the Second International Forum on Applications of Neural Networks to Power Systems\",\"volume\":\"21 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1993-04-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"[1993] Proceedings of the Second International Forum on Applications of Neural Networks to Power Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ANN.1993.264323\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"[1993] Proceedings of the Second International Forum on Applications of Neural Networks to Power Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ANN.1993.264323","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

摘要

本文描述了一种应用神经网络方法预测降雨后河流流量的尝试。作者使用了一个由三层组成的感知器类型的网络。神经网络的输入数据是降雨量和随后的河流流量。此外,所预测的降雨总量和持续时间作为附加输入数据。神经网络的输出是对河流流量的预测。研究发现,利用神经元的线性输入输出关系,可以提高神经网络的预测精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of artificial neural network to forecasting methods of time variation of the flow rate into a dam for a hydro-power plant
This paper describes an attempt to apply a neural network method to forecast river flow rate following a fall of rain. The authors use a perceptron-type network comprised of three layers. The input data to the neural network are rainfall amounts and subsequent river flow rates. Further the predicted total volume and duration of the spell of rainfall in question are taken as additional input data. The output from the neural network is forecasted river flow rate. It is found from these investigations that the forecasting accuracy of the neural network is improved by utilization of the linear input-output relations of neurons.<>
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