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 …

Background: Authors have been advocating the research ideology that a computer-aided
diagnosis (CAD) system trained using lots of patient data and physiological signals and …

The vast majority of today's data is collected and stored in enormous databases with a wide
range of characteristics that have little to do with the overarching goal concept. Feature …

This paper proposes a novel population-based optimization algorithm called Sine Cosine
Algorithm (SCA) for solving optimization problems. The SCA creates multiple initial random …

Feature selection (FS) has received significant attention since the use of a well-selected
subset of features may achieve better classification performance than that of full features in …

Feature selection is used to choose a subset of relevant features for effective classification of
data. In high dimensional data classification, the performance of a classifier often depends …

Feature selection is an important task for data analysis and information retrieval processing,
pattern classification systems, and data mining applications. It reduces the number of …

Abstract Ant Colony Optimization (ACO) and Bee Colony Optimization (BCO) are famous
meta-heuristic search algorithms used in solving numerous combinatorial optimization …

The slime mould algorithm is a stochastic optimization algorithm based on the oscillation
mode of nature's slime mould, and it has effective convergence. On the other hand, it gets …

Despite Grey Wolf Optimizer's (GWO) superior performance in many areas, stagnation in
local optima areas may still be a concern. Several significant GWO factors can be explored …