An adaptive Gaussian process based manifold transfer learning to expensive dynamic multi-objective optimization-Reference-Cited by-同舟云学术

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An adaptive Gaussian process based manifold transfer learning to expensive dynamic multi-objective optimization

Published:2023-06 Issue: Volume:538 Page:126212
ISSN:0925-2312
Container-title:Neurocomputing
language:en
Short-container-title:Neurocomputing

Author:

Zhang Xi,Yu Guo,Jin Yaochu,Qian Feng

Funder

National Natural Science Foundation of China

China Postdoctoral Science Foundation

Postdoctoral Science Foundation of Guangxi Province of China

Project 211

Higher Education Discipline Innovation Project

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference59 articles.

1. The effect of diversity maintenance on prediction in dynamic multi-objective optimization;Ruan;Applied Soft Computing,2017

2. A dynamic multi-objective optimization evolutionary algorithm for complex environmental changes;Liu;Knowledge-Based Systems,2021

3. Population-based incremental learning with associative memory for dynamic environments;Yang;IEEE Transactions on Evolutionary Computation,2008

4. Memory-enhanced dynamic multi-objective evolutionary algorithm based on Lp decomposition;Xu;Applied Sciences,2018

5. Knowledge guided Bayesian classification for dynamic multi-objective optimization;Ye;Knowledge-Based Systems,2022

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