应用聚类算法降低基础设施复原力预测模型的维度
IF 2.6
3区 工程技术
Q2 ENGINEERING, CIVIL
引用次数: 0
摘要
最近的研究越来越多地采用基于模拟的机器学习（ML）模型来分析关键基础设施系统的复原力。在现实应用中，这些 ML 模型考虑了...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 clustering algorithms for dimensionality reduction in infrastructure resilience prediction models
Recent studies increasingly adopt simulation-based machine learning (ML) models to analyse critical infrastructure system resilience. For realistic applications, these ML models consider the compon...
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来源期刊
Structure and Infrastructure Engineering
工程技术-工程：机械
CiteScore
9.50
自引率
8.10%
发文量
131
审稿时长
5.3 months
期刊介绍：
Structure and Infrastructure Engineering - Maintenance, Management, Life-Cycle Design and Performance is an international Journal dedicated to recent advances in maintenance, management and life-cycle performance of a wide range of infrastructures, such as: buildings, bridges, dams, railways, underground constructions, offshore platforms, pipelines, naval vessels, ocean structures, nuclear power plants, airplanes and other types of structures including aerospace and automotive structures.
The Journal presents research and developments on the most advanced technologies for analyzing, predicting and optimizing infrastructure performance. The main gaps to be filled are those between researchers and practitioners in maintenance, management and life-cycle performance of infrastructure systems, and those between professionals working on different types of infrastructures. To this end, the journal will provide a forum for a broad blend of scientific, technical and practical papers. The journal is endorsed by the International Association for Life-Cycle Civil Engineering ( IALCCE) and the International Association for Bridge Maintenance and Safety ( IABMAS).
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