Feature Selection (FS) methods alleviate key problems in classification procedures as they
are used to improve classification accuracy, reduce data dimensionality, and remove …

Twitter has become a major social media platform and has attracted considerable interest
among researchers in sentiment analysis. Research into Twitter Sentiment Analysis (TSA) is …

This paper proposes a novel population-based optimization method, called Aquila Optimizer
(AO), which is inspired by the Aquila's behaviors in nature during the process of catching the …

Evolutionary feature selection (FS) methods face the challenge of “curse of dimensionality”
when dealing with high-dimensional data. Focusing on this challenge, this article studies a …

The availability of accurate day-ahead electricity price forecasts is pivotal for electricity
market participants. In the context of trade liberalisation and market harmonisation in the …

Feature selection is a process to reduce the dimension of a dataset by removing redundant
features, and to use the optimal subset of features for machine learning or data mining …

In this paper, we present the swarm intelligence (SI) concept and mention some
metaheuristics belonging to the SI. We present the particle swarm optimization (PSO) …

In this research, we propose an intelligent decision support system for skin cancer detection.
Since generating an effective lesion representation is a vital step to ensure the success of …

In this study, we propose an improved version of the adaptive neuro-fuzzy inference system
(ANFIS) for forecasting the air quality index in Wuhan City, China. We propose a hybrid …

In the real world, there are a number of optimization problems whose search space is
restricted to take binary values; however, there are many continuous metaheuristics with …