Meta-heuristic algorithms have a high position among academic researchers in various
fields, such as science and engineering, in solving optimization problems. These algorithms …

Multilevel Thresholding (MLT) is considered as a significant and imperative research field in
image segmentation that can efficiently resolve difficulties aroused while analyzing the …

In this study, a neuro-fuzzy-based machine learning method is developed to predict the
multiaxial fatigue life of various metallic materials. First, the fuzzy inference system and …

The optimal reactive power dispatch (ORPD) problem plays an important role in the
reliability and economy of a power system. At present, the methods for solving the ORPD …

This paper presents a chaos-opposition-enhanced slime mould algorithm (CO-SMA) to
minimize energy (COE) cost for the wind turbines on high-altitude sites. The COE model is …

In this paper, we propose EOSMA, an equilibrium optimizer (EO)-guided slime mould
algorithm (SMA), to improve efficiency by optimizing the search of SMAs. Firstly, the …

This paper aims to represent a multi-objective equilibrium optimizer slime mould algorithm
(MOEOSMA) to solve real-world constraint engineering problems. The proposed algorithm …

An improved slime mould algorithm (ISMA) is proposed and applied to the size optimization
of truss structures with natural frequency constraints. The slime mould algorithm is a recently …

Existing data acquisition technologies desire further improvement to meet the increasing
need for big, accurate, and high‐quality data collection. Most of the collected data have …

The slime mould algorithm (SMA) is a metaheuristic algorithm recently proposed, which is
inspired by the oscillations of slime mould. Similar to other algorithms, SMA also has some …