The RIME optimization algorithm is a newly developed physics-based optimization algorithm
used for solving optimization problems. The RIME algorithm proved high-performing in …

Multiple kernel fuzzy clustering (MKFC) has demonstrated promising performance in
capturing the non-linear relationships within data. However, its effectiveness relies heavily …

Rime optimization algorithm (RIME) encounters issues such as an imbalance between
exploitation and exploration, susceptibility to local optima, and low convergence accuracy …

Metaheuristic algorithms are highly popular in the field of optimization because of their
gradient-free nature and strong applicability. Grey Wolf Optimizer (GWO for short) performs …

Aiming at the high dimension and complexity of parameters identification problem, a whale
optimization algorithm based on event-triggered and dimension learning scheme (EDWOA) …

This paper introduces a novel meta-heuristic algorithm named Rhinopithecus Swarm
Optimization (RSO) to address optimization problems, particularly those involving high …

Feature selection is crucial in data preprocessing, especially in medical data analysis.
Although the Grey Wolf Optimization (GWO) algorithm has attracted attention because of its …

Taking into account the whale optimization algorithm's tendency to get trapped in local
optima easily and its slow convergence rate, this paper proposes a diverse strategies whale …

The focus of consumer desire transitions from product functionality to emotional resonance
in experience economy era, wherein emotional needs of users increasingly become a …

With the increasing dimensionality of the data, High-dimensional Feature Selection (HFS)
becomes an increasingly difficult task. It is not simple to find the best subset of features due …