The use of machine learning-based techniques has expanded to many areas that require
optimization. One of such area is Integrated Circuit (IC) design and sizing optimization …

We propose a new fault diagnosis model for rolling bearings based on a hybrid kernel
support vector machine (SVM) and Bayesian optimization (BO). The model uses discrete …

Bayesian optimization is a popular method for sample efficient multi-objective optimization.
However, existing Bayesian optimization techniques fail to effectively exploit common and …

This study proposed a procedure to optimize the mixture proportion of geopolymer using
machine learning (ML) and multi-objective optimization (MOO) model, which enhances the …

Hyperparameter optimization (HPO) is crucial for strong performance of deep learning
algorithms and real-world applications often impose some constraints, such as memory …

Phased Array Antenna (PAA) technology plays an important role in fields such as radar, 5G
and satellite or any application which requires wide bandwidth and high gain. However …

Second-hand housing transactions constitute a significant segment of the real estate market
and are vital for its robust development. The dynamics of these transactions mirror the …

This paper addresses the problem of constrained multi-objective optimization over black-box
objective functions with practitioner-specified preferences over the objectives when a large …

Fake news detection is the process of identifying news that contain purposeful
misinformation disseminated through traditional news sources or social media platforms …

The management of water quality plays a pivotal role in fostering sustainable development,
especially in areas where groundwater serves as a vital resource for agricultural purposes …