From the past few decades many nature inspired algorithms have been developed and
gaining more popularity because of their effectiveness in solving problems of distinct …

This survey is an effort to provide a research repository and a useful reference for
researchers to guide them when planning to develop new Nature-inspired Algorithms …

The slime mould algorithm (SMA) is a logical swarm-based stochastic optimizer that is easy
to understand and has a strong optimization capability. However, the SMA is not suitable for …

One of the major problems in Big Data is a large number of features or dimensions, which
causes the issue of “the curse of dimensionality” when applying machine learning …

Feature selection is an important task in data mining and machine learning to reduce the
dimensionality of the data and increase the performance of an algorithm, such as a …

Featured Application The paper analyzes the usage and mechanisms of feature selection
methods that are based on swarm intelligence in different application areas. Abstract The …

Over recent years, there has been a rapid development of deep learning (DL) in both
industry and academia fields. However, finding the optimal hyperparameters of a DL model …

Over the past two decades, the feedforward neural network (FNN) optimization has been a
key interest among the researchers and practitioners of multiple disciplines. The FNN …

The main objective of the present study was to provide a novel methodological approach for
flash flood susceptibility modeling based on a feature selection method (FSM) and tree …

Seagull optimization algorithm (SOA) is a recent bio-inspired technique utilized to improve
the constrained large-scale problems in low computational cost and quick convergence …