Multivariable teaching-learning-based optimization (MTLBO) algorithm for estimating the structural parameters of the buried mass by magnetic data

IF 0.9 4区 地球科学 Q4 GEOCHEMISTRY & GEOPHYSICS
Geofizika Pub Date : 2020-12-23 DOI:10.15233/gfz.2020.37.6
A. Eshaghzadeh, S. S. Sahebari
{"title":"Multivariable teaching-learning-based optimization (MTLBO) algorithm for estimating the structural parameters of the buried mass by magnetic data","authors":"A. Eshaghzadeh, S. S. Sahebari","doi":"10.15233/gfz.2020.37.6","DOIUrl":null,"url":null,"abstract":"This paper presents a nature-based algorithm, titled multivariable teaching-learning-based optimization (MTLBO) algorithm. MTLBO algorithm during an iterative process can estimates the best values of the buried structure (model) parameters in a multi-objective problem. The algorithm works in two computational phases: the teacher phase and the learner phase. The major purpose of the MTLBO algorithm is to modify the value of the learners and thus, improving the value of the model parameters which leads to the optimal solution. The variables of each learner (model) are the depth (z), amplitude coefficient (k), shape factor (q), angle of effective magnetization (θ) and axis location (x0) parameters. We employ MTLBO method for the magnetic anomalies caused by the buried structures with a simple geometric shape such as sphere and horizontal cylinder. The efficiency of the MTLBO is also studied by noise corruption synthetic data, as the acceptable results were obtained. We have applied the MTLBO for the interpretation of the four magnetic anomaly profiles from Iran, Brazil and India.","PeriodicalId":50419,"journal":{"name":"Geofizika","volume":null,"pages":null},"PeriodicalIF":0.9000,"publicationDate":"2020-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Geofizika","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.15233/gfz.2020.37.6","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"GEOCHEMISTRY & GEOPHYSICS","Score":null,"Total":0}
引用次数: 1

Abstract

This paper presents a nature-based algorithm, titled multivariable teaching-learning-based optimization (MTLBO) algorithm. MTLBO algorithm during an iterative process can estimates the best values of the buried structure (model) parameters in a multi-objective problem. The algorithm works in two computational phases: the teacher phase and the learner phase. The major purpose of the MTLBO algorithm is to modify the value of the learners and thus, improving the value of the model parameters which leads to the optimal solution. The variables of each learner (model) are the depth (z), amplitude coefficient (k), shape factor (q), angle of effective magnetization (θ) and axis location (x0) parameters. We employ MTLBO method for the magnetic anomalies caused by the buried structures with a simple geometric shape such as sphere and horizontal cylinder. The efficiency of the MTLBO is also studied by noise corruption synthetic data, as the acceptable results were obtained. We have applied the MTLBO for the interpretation of the four magnetic anomaly profiles from Iran, Brazil and India.
基于多变量教-学优化(MTLBO)算法的地磁资料结构参数估计
本文提出了一种基于自然的多变量教-学优化算法(MTLBO)。MTLBO算法在迭代过程中可以估计出多目标问题中埋地结构(模型)参数的最优值。该算法分为两个计算阶段:教师阶段和学习者阶段。MTLBO算法的主要目的是修改学习器的值,从而提高模型参数的值,从而得到最优解。每个学习器(模型)的变量是深度(z)、振幅系数(k)、形状因子(q)、有效磁化角(θ)和轴位置(x0)参数。本文采用MTLBO方法对球面、水平圆柱体等简单几何形状的地下构造引起的磁异常进行了分析。通过噪声损坏合成数据对MTLBO的效率进行了研究,得到了可接受的结果。应用MTLBO对伊朗、巴西和印度的4条磁异常剖面进行了解释。
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
Geofizika
Geofizika 地学-地球化学与地球物理
CiteScore
1.60
自引率
0.00%
发文量
17
审稿时长
>12 weeks
期刊介绍: The Geofizika journal succeeds the Papers series (Radovi), which has been published since 1923 at the Geophysical Institute in Zagreb (current the Department of Geophysics, Faculty of Science, University of Zagreb). Geofizika publishes contributions dealing with physics of the atmosphere, the sea and the Earth''s interior.
×
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