For the problems of Grey wolf optimizer (GWO) easy to fall into local optimum and lack of
population diversity, this thesis raises a Grey wolf optimizer combined with an Artificial fish …

Optimisation-based methods are enormously used in the field of data classification. Particle
Swarm Optimization (PSO) is a metaheuristic algorithm based on swarm intelligence, widely …

In response to the need to generate synthetic minority class samples to extend minority
classes, the SMOTE-based oversampling methods have been favored for class-imbalanced …

To address the problems of bald eagle search algorithm (BES), easy fall into local optimums,
limited diversity and slow convergence, a dynamic ensemble multi-strategy bald eagle …

Hyperspectral images contain large spectral information with an abundance of redundancy
and a curse of dimensionality. Due to the absence of prior knowledge or availability of …

Practical issues in real-world engineering problems limit the use of traditional optimization
methods in finding solutions to design optimization problems. Although several advanced …

Inter-story isolation systems, as an alternative earthquake protection system, reduce in-
building movement compared to base isolation systems. In this context, the current study …

Neuro-fuzzy systems show promise for adaptive control but can become complex due to the
need to learn many parameters. This paper presents a resilient nonlinear controller that …

This paper proposes and evaluates a novel control approach for trajectory tracking, stability
enhancement, and vibration reduction of a flexible joint robot (FJR). The FJR is a 2-degree …

The self-labeled methods can enlarge the labeled set by continuously adding pseudo-
labeled data from the unlabeled set and predicted by base classifiers. Mislabeling is a great …