This paper presents an in‐depth survey and performance evaluation of cat swarm
optimization (CSO) algorithm. CSO is a robust and powerful metaheuristic swarm‐based …

Swarm based optimization algorithms are a collection of intelligent techniques in the field of
Artificial Intelligence (AI) were developed for simulating the intelligent behavior of animals …

Reasonable capacity configuration of wind farm, photovoltaic power station and energy
storage system is the premise to ensure the economy of wind-photovoltaic-storage hybrid …

The Graph Coloring Problem (GCP) is a significant optimization challenge widely suitable to
solve scheduling problems. Its goal is to specify the minimum colors (k) required to color a …

Feature selection, which is a type of optimization problem, is generally achieved by
combining an optimization algorithm with a classifier. Genetic algorithms and particle swarm …

Sentiment analysis is crucial in various systems such as opinion mining and predicting.
Considerable research has been done to analyze sentiment using various machine learning …

This paper presents a cat swarm optimization (CSO) algorithm for solving global
optimization problems. In CSO algorithm, some modifications are incorporated to improve its …

In this contribution we present the application of a hybrid cat swarm optimization (CSO)
based algorithm for solving the school timetabling problem. This easy to use, efficient and …

The classification accuracy of a multi-layer perceptron (MLP) depends on the selection of
relevant features from the data set, its architecture, connection weights and the transfer …

The problem that is being solved in the research is to increase the efficiency of decision-
making in management tasks while ensuring the given reliability, regardless of the …