Memory-based sand cat swarm optimization for feature selection in medical diagnosis
The rapid expansion of medical data poses numerous challenges for Machine Learning
(ML) tasks due to their potential to include excessive noisy, irrelevant, and redundant …
(ML) tasks due to their potential to include excessive noisy, irrelevant, and redundant …
DGS-SCSO: enhancing sand cat swarm optimization with dynamic pinhole imaging and golden sine algorithm for improved numerical optimization performance
This paper introduces DGS-SCSO, a novel optimizer derived from Sand Cat Swarm
Optimization (SCSO), aiming to overcome inherent limitations in the original SCSO …
Optimization (SCSO), aiming to overcome inherent limitations in the original SCSO …
[HTML][HTML] A bioinspired discrete heuristic algorithm to generate the effective structural model of a program source code
When the source code of a software is the only product available, program understanding
has a substantial influence on software maintenance costs. The main goal in code …
has a substantial influence on software maintenance costs. The main goal in code …
Email Spam Detection by Machine Learning Approaches: A Review
MT Hadi, SS Baawi - … on Forthcoming Networks and Sustainability in the …, 2024 - Springer
Currently, technology has exhibited substantial advancement, resulting in the improvement
of communication. Emails are often regarded as the most effective method for both informal …
of communication. Emails are often regarded as the most effective method for both informal …
Parallel binary rafflesia optimization algorithm and its application in feature selection problem
The Rafflesia Optimization Algorithm (ROA) is a new swarm intelligence optimization
algorithm inspired by Rafflesia's biological laws. It has the advantages of high efficiency and …
algorithm inspired by Rafflesia's biological laws. It has the advantages of high efficiency and …
IMSCSO: An Intensified Sand Cat Swarm Optimization with Multi-Strategy for Solving Global and Engineering Optimization Problems
X Li, Y Qi, Q Xing, Y Hu - IEEE Access, 2023 - ieeexplore.ieee.org
Optimization challenges are becoming more complex as the world advances. Since
deterministic and heuristic approaches are no longer sufficient to deal with such complex …
deterministic and heuristic approaches are no longer sufficient to deal with such complex …
Sahand 1.0: A new model for extracting information from source code in object-oriented projects
GNH Irani, H Izadkhah - Computer Standards & Interfaces, 2024 - Elsevier
Providing models that enable developers, architects, and executives to make intelligent
decisions about software projects is imperative. Static analyzer tools can extract the …
decisions about software projects is imperative. Static analyzer tools can extract the …
Human Activity Recognition Using Convolutional Neural Networks
This research addresses human activity recognition (HAR) using a deep learning
framework. Particularly convolutional neural networks (CNNs) to identify and categorize …
framework. Particularly convolutional neural networks (CNNs) to identify and categorize …
A Modified Horse Herd Optimization Algorithm and Its Application in the Program Source Code Clustering
Maintenance is one of the costliest phases in the software development process. If
architectural design models are accessible, software maintenance can be made more …
architectural design models are accessible, software maintenance can be made more …
Advances in Sand Cat Swarm Optimization: A Comprehensive Study
F Anka, N Aghayev - Archives of Computational Methods in Engineering, 2025 - Springer
This study provides an in-depth review and analysis of the nature-inspired Sand Cat Swarm
Optimization (SCSO) algorithm. The SCSO algorithm effectively focuses on exploring …
Optimization (SCSO) algorithm. The SCSO algorithm effectively focuses on exploring …