Despite the availability and ease of collecting a large amount of free, unlabeled data, the
expensive and time-consuming labeling process is still an obstacle to labeling a sufficient …

Over past few decades, as a powerful analytical tool to characterize the fitness landscape of
a problem, fitness landscape analysis (FLA) has been widely concerned and utilized for all …

The grey wolf optimizer is an effective and well-known meta-heuristic algorithm, but it also
has the weaknesses of insufficient population diversity, falling into local optimal solutions …

This paper proposes a strengthened RIME algorithm to tackle continuous optimization
problems. RIME is a newly proposed physical-based evolutionary algorithm (EA) inspired by …

The balance between multiple objectives and various constraints is the key to solving
constrained multi-objective optimization problems (CMOPs). When dealing with CMOPs with …

In the realm of ocean engineering and environmental research, the accuracy of the wave
spectrum is paramount. Traditional models, constrained by the number of parameters, often …

Analyzing large datasets to select optimal features is one of the most important research
areas in machine learning and data mining. This feature selection procedure involves …

The exponential growth of technology and advent of the Internet of Things (IoT) paradigm
have caused large volumes of data to be continuously generated from the intelligent …

A large number of metaheuristic algorithms have been proposed in the last three decades,
but no metaheuristic algorithm is superior to the others for all the optimization problems. It is …

Roundness error is one of the core indicators for evaluating the geometric accuracy of round
parts mechanical products, directly affecting product performance and service life. In the field …