Elephant herding optimization (EHO) is a nature-inspired metaheuristic optimization
algorithm based on the herding behavior of elephants. EHO uses a clan operator to update …

Metaheuristic algorithms are extensively utilized to find solutions and optimize complex
industrial systems' performance. In this paper, metaheuristic algorithms are utilized to predict …

This study aims to propose an efficient evaluation model for Sino foreign cooperative
education projects, which can offer a reasonable reference for universities to deepen reform …

Federated learning is a learning method that collects only learned models on a server to
ensure data privacy. This method does not collect data on the server but instead proceeds …

This paper presents an approach to design convolutional neural network architectures,
using the particle swarm optimization algorithm. The adjustment of the hyper-parameters …

Classification of imbalanced datasets has attracted substantial research interest over the
past decades. Imbalanced datasets are common in several domains such as health, finance …

This article proposes a framework that automatically designs classifiers for the early
detection of COVID-19 from chest X-ray images. To do this, our approach repeatedly makes …

This study proposes an effective intelligent predictive model for prediction of cervical
hyperextension injury. The prediction model is constructed by combing an improved sine …

Abstract Generally, the Particle Swarm Optimization (PSO) algorithm has two memory
dimensions: cognitive and social. In this study, a new dimension called family memory has …

The design of reinforced earth retaining walls is a combinatorial optimization problem of
interest due to practical applications regarding the cost savings involved in the design and …