The partitional clustering concept started with K-means algorithm which was published in
1957. Since then many classical partitional clustering algorithms have been reported based …

Abstract Gravitational Search Algorithm (GSA) is an optimization method inspired by the
theory of Newtonian gravity in physics. Till now, many variants of GSA have been …

This paper presents a novel Reinforcement Learning (RL)-based control approach that uses
a combination of a Deep Q-Learning (DQL) algorithm and a metaheuristic Gravitational …

Feature selection is one of the most efficient procedures for reducing the dimensionality of
high-dimensional data by choosing a practical subset of features. Since labeled samples are …

Abstract Ant Colony Optimization (ACO) is a probabilistic and approximation metaheuristic
algorithm to solve complex combinatorial optimization problems. ACO algorithm is inspired …

In recent years, various heuristic optimization methods have been developed. Many of these
methods are inspired by swarm behaviors in nature. In this paper, a new optimization …

Intradialytic hypotension (IDH) is the most common acute complication in hemodialysis (HD)
sessions and is associated with increased morbidity and mortality in HD patients. To prevent …

Fault detection, isolation and optimal control have long been applied to industry. These
techniques have proven various successful theoretical results and industrial applications …

Data clustering is a popular analysis tool for data statistics in many fields such as pattern
recognition, data mining, machine learning, image analysis, and bioinformatics. The aim of …

To improve the exploration and exploitation abilities of the standard Gravitational Search
Algorithm (GSA), a novel operator called “Disruption”, originating from astrophysics, is …