hvarma:微颤H/V谱比的自回归移动平均模型

IF 1.3 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING
Aleix Seguí , Arantza Ugalde , Juan José Egozcue
{"title":"hvarma:微颤H/V谱比的自回归移动平均模型","authors":"Aleix Seguí ,&nbsp;Arantza Ugalde ,&nbsp;Juan José Egozcue","doi":"10.1016/j.simpa.2025.100745","DOIUrl":null,"url":null,"abstract":"<div><div>hvarma is a Python software for estimating the horizontal-to-vertical (<em>H</em>/<em>V</em>) spectral ratio through seismic ambient vibration measurements. It employs a parametric approach to model the <em>H</em>/<em>V</em> transfer function using an AutoRegressive Moving Average (ARMA) filter. Compared to traditional methods, this technique enhances accuracy and reliability in spectral estimates, determining the ground fundamental resonance frequency with high spectral resolution, which is important for engineering geology projects. The program inverts to find optimal filter coefficients and computes coherence between horizontal and vertical components, generating <em>H</em>/<em>V</em> transfer function visualizations across both negative and positive frequencies. Results are saved as image and text files.</div></div>","PeriodicalId":29771,"journal":{"name":"Software Impacts","volume":"23 ","pages":"Article 100745"},"PeriodicalIF":1.3000,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"hvarma: Autoregressive moving average model of microtremor H/V spectral ratio\",\"authors\":\"Aleix Seguí ,&nbsp;Arantza Ugalde ,&nbsp;Juan José Egozcue\",\"doi\":\"10.1016/j.simpa.2025.100745\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>hvarma is a Python software for estimating the horizontal-to-vertical (<em>H</em>/<em>V</em>) spectral ratio through seismic ambient vibration measurements. It employs a parametric approach to model the <em>H</em>/<em>V</em> transfer function using an AutoRegressive Moving Average (ARMA) filter. Compared to traditional methods, this technique enhances accuracy and reliability in spectral estimates, determining the ground fundamental resonance frequency with high spectral resolution, which is important for engineering geology projects. The program inverts to find optimal filter coefficients and computes coherence between horizontal and vertical components, generating <em>H</em>/<em>V</em> transfer function visualizations across both negative and positive frequencies. Results are saved as image and text files.</div></div>\",\"PeriodicalId\":29771,\"journal\":{\"name\":\"Software Impacts\",\"volume\":\"23 \",\"pages\":\"Article 100745\"},\"PeriodicalIF\":1.3000,\"publicationDate\":\"2025-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Software Impacts\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2665963825000053\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, SOFTWARE ENGINEERING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Software Impacts","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2665963825000053","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
引用次数: 0

摘要

hvarma是一个Python软件,用于通过地震环境振动测量估计水平与垂直(H/V)频谱比。它采用参数化方法使用自回归移动平均(ARMA)滤波器对H/V传递函数建模。与传统方法相比,该技术提高了频谱估计的精度和可靠性,以高光谱分辨率确定了地面基共振频率,对工程地质工程具有重要意义。该程序通过反向查找最佳过滤系数,并计算水平和垂直分量之间的相干性,从而在负频率和正频率上生成H/V传递函数可视化。结果保存为图像和文本文件。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
hvarma: Autoregressive moving average model of microtremor H/V spectral ratio
hvarma is a Python software for estimating the horizontal-to-vertical (H/V) spectral ratio through seismic ambient vibration measurements. It employs a parametric approach to model the H/V transfer function using an AutoRegressive Moving Average (ARMA) filter. Compared to traditional methods, this technique enhances accuracy and reliability in spectral estimates, determining the ground fundamental resonance frequency with high spectral resolution, which is important for engineering geology projects. The program inverts to find optimal filter coefficients and computes coherence between horizontal and vertical components, generating H/V transfer function visualizations across both negative and positive frequencies. Results are saved as image and text files.
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
Software Impacts
Software Impacts Software
CiteScore
2.70
自引率
9.50%
发文量
0
审稿时长
16 days
×
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:604180095
Book学术官方微信