Special Issue

Topic: Adaptive Surrogate Modeling for Reliability Evaluation and Multidisciplinary Design Optimization
A Special Issue of Complex Engineering Systems
ISSN 2770-6249 (Online)
Submission deadline: 31 Dec 2024
Guest Editors
Special Issue Introduction
The surrogate model method is a model approximation technology based on experimental design for handling multi-variable and complex engineering modeling analysis. Its adaptive process automatically adjusts and supplements model processing parameters and approaches based on the data characteristics of known sample points when investigating the model characteristics of unknown areas. This makes it consistent with the statistical distribution characteristics of the target data to be processed or its structural characteristics. The modeling technique based on the adaptive surrogate model can use a smaller number of samples to predict its failure probability with higher accuracy, improving computing efficiency and significantly reducing computing costs. It has important theoretical and engineering application value in the reliability assessment of complex structures and multidisciplinary design optimization research.
The proposed Special Issue endeavors to build an academic communication platform to promote the innovative development of adaptive surrogate model methods in the fields of reliability assessment and multidisciplinary design optimization. Potential topics include, but are not limited to:
● Modeling methods;
● Adaptive surrogate models;
● Structure integrity;
● Structural reliability;
● Reliability evaluation methods;
● Optimization methods;
● Multiple failure modes;
● Prediction and health management;
● Machine learning;
● Artificial intelligence;
● Heuristic algorithms;
● Reliability-based multidisciplinary design optimization.
Keywords
Submission Deadline
Submission Information
For Author Instructions, please refer to https://www.oaepublish.com/comengsys/author_instructions
For Online Submission, please login at https://www.oaecenter.com/login?JournalId=comengsys&IssueId=comengsys2412311953
Submission Deadline: 31 Dec 2024
Contacts: Lyric Zhang, Assistant Editor, Lyric@oaeservice.com