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 …

As the COVID-19 pandemic rapidly spreads across the world, regrettably, misinformation
and fake news related to COVID-19 have also spread remarkably. Such misinformation has …

Feature Selection (FS) techniques extract the most recognizable features for improving the
performance of classification methods for medical applications. In this paper, two intelligent …

A process must be followed in order to attain useful information from the available data. The
Knowledge Discovery in the Database (KDD)[3] is a general structure that defines the steps …

This study relies on using a Moth–Flame Optimization (MFO) method as a search algorithm
and a Decision Tree (DT) as an evaluation algorithm to generate an efficient feature subset …

In this work, an enhanced moth flame optimization (MFO) algorithm is proposed as a search
strategy within a wrapper feature selection (FS) framework. It aims mainly to improve the …

Software defect prediction (SDP) is crucial in the early stages of defect-free software
development before testing operations take place. Effective SDP can help test managers …

Feature selection commonly refers to a process of using the candidate algorithm to detect
the optimal feature sets during the preprocessing steps in machine learning and data …

This paper proposes an effective wrapper approach by integrating the Levy flight and
evolutionary selection operators into the Moth Flame Optimization (MFO) algorithm. The …

Classification of medical data is largely dependent on the effective identification of key
features of the data that can be used to aid in the diagnosis of related diseases. This goal …