Grey Model with Rolling Mechanism for Radio-Wave Path-Loss Forecasting in Suburban Environment

IF 1 4区 工程技术 Q4 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Kuo-Chen Hung, Kuo-Ping Lin, Fu-Yuan Hsu, Chi-Kai Wang, Jen-Chang Lin
{"title":"Grey Model with Rolling Mechanism for Radio-Wave Path-Loss Forecasting in Suburban Environment","authors":"Kuo-Chen Hung, Kuo-Ping Lin, Fu-Yuan Hsu, Chi-Kai Wang, Jen-Chang Lin","doi":"10.30016/JGS.201006.0001","DOIUrl":null,"url":null,"abstract":"The grey prediction model, GM (1,1), with the property of processing with a minimum of data, has been successfully applied in various fields. However, applying grey prediction with rolling mechanism (GPRM) to predict radio-wave path-loss has not been widely investigated. Thus, this paper aims applying GPRM approach for the prediction of radio-wave path loss in suburban environment. Furthermore, a comparison has been discussed with traditional other radio-wave path-loss prediction approaches and the proposed approach. An illustrative example, we find that the GPRM method can effectively fitting the actual value than other current models. Consequently, this method can help designer to evaluate radio-wave path-loss in uncertain environment.","PeriodicalId":50187,"journal":{"name":"Journal of Grey System","volume":"13 1","pages":"49-53"},"PeriodicalIF":1.0000,"publicationDate":"2010-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Grey System","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.30016/JGS.201006.0001","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"MATHEMATICS, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 2

Abstract

The grey prediction model, GM (1,1), with the property of processing with a minimum of data, has been successfully applied in various fields. However, applying grey prediction with rolling mechanism (GPRM) to predict radio-wave path-loss has not been widely investigated. Thus, this paper aims applying GPRM approach for the prediction of radio-wave path loss in suburban environment. Furthermore, a comparison has been discussed with traditional other radio-wave path-loss prediction approaches and the proposed approach. An illustrative example, we find that the GPRM method can effectively fitting the actual value than other current models. Consequently, this method can help designer to evaluate radio-wave path-loss in uncertain environment.
基于滚动机制的城郊无线电波路径损耗预测灰色模型
灰色预测模型GM(1,1)具有数据量最少的特点,已成功应用于各个领域。然而,应用滚动机制灰色预测(GPRM)预测无线电波路径损耗的方法尚未得到广泛的研究。因此,本文旨在将GPRM方法应用于城郊环境下的无线电波路径损耗预测。此外,还与传统的其他无线电波路径损耗预测方法进行了比较。算例表明,GPRM方法比现有的其他模型更能有效地拟合实际值。因此,该方法可以帮助设计者评估不确定环境下的无线电波路径损耗。
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
Journal of Grey System
Journal of Grey System 数学-数学跨学科应用
CiteScore
2.40
自引率
43.80%
发文量
0
审稿时长
1.5 months
期刊介绍: The journal is a forum of the highest professional quality for both scientists and practitioners to exchange ideas and publish new discoveries on a vast array of topics and issues in grey system. It aims to bring forth anything from either innovative to known theories or practical applications in grey system. It provides everyone opportunities to present, criticize, and discuss their findings and ideas with others. A number of areas of particular interest (but not limited) are listed as follows: Grey mathematics- Generator of Grey Sequences- Grey Incidence Analysis Models- Grey Clustering Evaluation Models- Grey Prediction Models- Grey Decision Making Models- Grey Programming Models- Grey Input and Output Models- Grey Control- Grey Game- Practical Applications.
×
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