A Fatigue Crack Length Estimation and Prediction using Trans-fitting with Support Vector Regression > International | 서울대학교 초자율화 인공지능 연구실

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Hyperautomation Artificial Intelligence

A Fatigue Crack Length Estimation and Prediction using Trans-fitting with Support Vector Regression

본문

Conference: Annual Conference of the Prognostics and Health Management Society 2019

Author: Myeongbaek Youn, Yunhan Kim, Dongki Lee, and Minki Cho

Date: 2019-09-25

Presentation Type: Oral

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이전글Multiple Defect Modes of a Phononic Crystal and Its Application to Broadband Piezoelectric Energy Harvesting 24.05.03
다음글A Hybrid Approach of Data-driven and Physics-based Methods for Estimation and Prediction of Fatigue Crack Growth 24.05.03