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 …

Machine learning and data mining have established several effective applications in gene
selection analysis. This paper review semi-supervised learning algorithms and gene …

Recently, many optimization algorithms have been applied for Feature selection (FS)
problems and show a clear outperformance in comparison with traditional FS methods …

Advancements in medical technology have created numerous large datasets including
many features. Usually, all captured features are not necessary, and there are redundant …

Whale optimization algorithm (WOA) is a newly developed meta-heuristic algorithm, which is
mainly based on the predation behavior of humpback whales in the ocean. In this paper, a …

In order to realize the performance of the PV model before being installed, it is often
indispensable to develop reliable and accurate parameter identification methods for dealing …

Several feature selection methods have been developed to extract the optimal features from
a dataset in medical datasets classification. Creating an efficient technique has become a …

Feature Selection (FS) reduces the number of features by removing unnecessary,
redundant, and noisy information while kee** a relatively decent classification accuracy …

Dragonfly Algorithm (DA) is a recent swarm-based optimization method that imitates the
hunting and migration mechanisms of idealized dragonflies. Recently, a binary DA (BDA) …

Segmentation is a crucial phase in image processing because it simplifies the
representation of an image and facilitates its analysis. The multilevel thresholding method is …