Bias-variance tradeoff in machine learning: Theoretical formulation and implications to structural engineering applications
Author:
Funder
National Science Foundation
Publisher
Elsevier BV
Subject
Safety, Risk, Reliability and Quality,Building and Construction,Architecture,Civil and Structural Engineering
Reference49 articles.
1. A data-driven physics-informed method for prognosis of infrastructure systems: Theory and application to crack prediction;Das;ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering,2020
2. Data-driven optimal predictive control of seismic induced vibrations in frame structures;Di Girolamo;Structural Control and Health Monitoring,2020
3. Esteghamati MZ, Flint MM. Developing data-driven surrogate models for holistic performance-based assessment of mid-rise RC frame buildings at early design. Engineering Structures 2021;245:112971.
4. A data-driven framework for near real-time and robust damage diagnosis of building structures;Sajedi;Structural Control and Health Monitoring,2020
5. Sen D, Long J, Sun H, Campman X, Buyukozturk O. Multi-component deconvolution interferometry for data-driven prediction of seismic structural response. Engineering Structures 2021;241:112405.
Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Ensemble of classifiers based on score function defined by clusters and decision boundary of linear base learners;Knowledge-Based Systems;2024-11
2. Using the polynomial chaos expansion and bias-variance tradeoff to analyse the statistical characteristics of a trimaran cross-deck structure;Marine Structures;2024-11
3. Generalizability evaluations of heterogeneous ensembles for river health predictions;Ecological Informatics;2024-09
4. Application of polynomial chaos expansion in sensitivity analysis of towed cable parameters of the underwater towing system;Journal of Ocean Engineering and Science;2023-09
5. Do all roads lead to Rome? A comparison of knowledge-based, data-driven, and physics-based surrogate models for performance-based early design;Engineering Structures;2023-07
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3