.png){kind=icon}
Return
Evolutionary dynamic multiobjective optimization using a Bayesian vector autoregression prediction model
.png){kind=icon}
PRE
AI
DOI：10.1016/j.engappai.2025.111696.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
• A dynamic multiobjective optimization evolutionary algorithm is proposed. • A Bayesian vector autoregression model is applied to predict the initial population. • Multivariate interaction optimization significantly improves the search efficiency. • Systematic studies demonstrate the effectiveness of the proposed algorithm.
Journal
IF:
8
Papers:
5.7K
Citations:
3.5W
Organization
No organization information available
Cited Papers
ShareSaveDynamic Multiobjective Squirrel Search Algorithm Based on Decomposition With Evolutionary Direction Prediction and Bidirectional Memory Populations.png)
IEEE ACCESS
OAAI
IEEE ACCESSIF3.6
OAAIShareSaveShareSaveElectrohydrodynamics-Printed Silver Nanoparticle Flexible Pressure Sensors With Improved Gauge FactorIEEE SENSORS JOURNAL
IEEE SENSORS JOURNALIF4.5
PREAI
ShareSaveShareSaveShareSave
View more