The utilization of surrogate models to approximate complex systems has recently gained increased popularity. Because of their capability to deal with black-box problems and lower …
Complex continuous optimization problems widely exist nowadays due to the fast development of the economy and society. Moreover, the technologies like Internet of things …
As an advanced artificial intelligence technique for solving learning problems, deep learning (DL) has achieved great success in many real-world applications and attracted increasing …
Y Hua, Q Liu, K Hao, Y Jin - IEEE/CAA Journal of Automatica …, 2021 - ieeexplore.ieee.org
Evolutionary algorithms have been shown to be very successful in solving multi-objective optimization problems (MOPs). However, their performance often deteriorates when solving …
Only a small number of function evaluations can be afforded in many real-world multiobjective optimization problems (MOPs) where the function evaluations are …
H Zhu, Y Jin - IEEE transactions on neural networks and …, 2019 - ieeexplore.ieee.org
Federated learning is an emerging technique used to prevent the leakage of private information. Unlike centralized learning that needs to collect data from users and store them …
Convolutional neural networks (CNNs) have shown remarkable performance in various real- world applications. Unfortunately, the promising performance of CNNs can be achieved only …
As the population in cities continues to increase, large-city problems, including traffic congestion and environmental pollution, have become increasingly serious. The …
J Tian, M Hou, H Bian, J Li - Complex & Intelligent Systems, 2023 - Springer
Many industrial applications require time-consuming and resource-intensive evaluations of suitable solutions within very limited time frames. Therefore, many surrogate-assisted …