A Hybrid Barnacles Mating Optimizer Algorithm With Support Vector Machines for Gene Selection of Microarray Cancer Classification

Houssein, Essam H.; AbdElminaam, Diaa Salama; Hassan, Hager N.; Al-Sayed, Mustafa M.; Nabil, Emad

doi:10.1109/access.2021.3075942

Cited by 63 publications

(25 citation statements)

References 31 publications

(39 reference statements)

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…General interactive genetic algorithm only supports single user evaluation. The results can only reflect the preferences of a single user [13]. The product designed by interactive genetic algorithm needs to meet the needs of as many users as possible [14].…”

Section: Introductionmentioning

confidence: 99%

Application of Multipopulation Genetic Algorithm in Industrial Special Clothing Design

Zhang¹,

Yang

2022

Wireless Communications and Mobile Computing

View full text Add to dashboard Cite

Industrial special clothing refers to the clothing worn by employees of industrial enterprises and departments in order to dress uniformly, facilitate work, or protect their bodies from external injuries. They have the common characteristics of practicality and identification. This kind of clothing includes many styles, such as uniforms, shirts, jackets, overalls, skirts, aprons, and headscarves, which are also applicable in different fields. For example, the clothing for high-temperature operation requires high temperature resistance and comfort, while the clothing for high-altitude operation requires high clothing strength and can play a protective role. General interactive genetic algorithm only supports single user evaluation. The results can only reflect the preferences of a single user. The product designed by interactive genetic algorithm needs to meet the needs of as many users as possible, and a multiuser interactive genetic algorithm suitable for population design is proposed. The detailed design of three main modules of the algorithm, namely, population initialization module, single population module, and multipopulation module, is given. Finally, the algorithm and the general single user interactive genetic algorithm are applied to the garment design system for comparative experiments. The effectiveness of the algorithm in group design is verified.

show abstract

Section: Introductionmentioning

confidence: 99%

Application of Multipopulation Genetic Algorithm in Industrial Special Clothing Design

Zhang¹,

Yang

2022

Wireless Communications and Mobile Computing

View full text Add to dashboard Cite

show abstract

“…Other deep learning [35][36][37][38][39][40][41][42] and optimization algorithms are also used to solve various optimization problems [43][44][45][46][47][48][49][50][51]. However, several gaps in using deep learning systems for real-time implementation and prevention strategies must be addressed, as indicated [52][53][54][55][56][57].…”

Section: Literature Reviewmentioning

confidence: 99%

Real-Time Facemask Detection for Preventing COVID-19 Spread Using Transfer Learning Based Deep Neural Network

Ali

Shanmugam²,

Muthusamy³

et al. 2022

Electronics

View full text Add to dashboard Cite

The COVID-19 pandemic disrupted people’s livelihoods and hindered global trade and transportation. During the COVID-19 pandemic, the World Health Organization mandated that masks be worn to protect against this deadly virus. Protecting one’s face with a mask has become the standard. Many public service providers will encourage clients to wear masks properly in the foreseeable future. On the other hand, monitoring the individuals while standing alone in one location is exhausting. This paper offers a solution based on deep learning for identifying masks worn over faces in public places to minimize the coronavirus community transmission. The main contribution of the proposed work is the development of a real-time system for determining whether the person on a webcam is wearing a mask or not. The ensemble method makes it easier to achieve high accuracy and makes considerable strides toward enhancing detection speed. In addition, the implementation of transfer learning on pretrained models and stringent testing on an objective dataset led to the development of a highly dependable and inexpensive solution. The findings provide validity to the application’s potential for use in real-world settings, contributing to the reduction in pandemic transmission. Compared to the existing methodologies, the proposed method delivers improved accuracy, specificity, precision, recall, and F-measure performance in three-class outputs. These metrics include accuracy, specificity, precision, and recall. An appropriate balance is kept between the number of necessary parameters and the time needed to conclude the various models.

show abstract

“…Existen las propuestas de otros modelos híbridos entre los AM y los DLA, pero su aplicación es distinta a la clasificación de AC. En particular solo mencionaremos dos; el desarrollado por (Navaneeth and Suchetha, 2019), que se fundamenta en el uso del PSO-CNN-MVS con el objetivo de clasificar enfermedades renales crónicas, y finalmente, (Houssein et al, 2021a) quiénes propusieron un modelo híbrido compuesto por el algoritmo optimizador de apareamiento de percebes con MVS, para la selección de genes en la clasificación de cáncer.…”

Section: Antecedentes Y Trabajo Relacionadounclassified

Clasificación de Arritmias Cardíacas mediante Redes Neuronales Convolucionales y Optimización por Enjambre de Partículas

Santander-Baños

Hernández-Romero

Barragan-Vite

et al. 2022

ICBI

View full text Add to dashboard Cite

Una arritmia cardíaca es un latido irregular del corazón que se traduce en un impulso eléctrico anormal, y su tipo se define por el ritmo y duración. Su clasificación ha sido abordada en diferentes campos de la ciencia, destacando el uso de algoritmos de aprendizaje profundo. La presente investigación, utilizó un modelo híbrido entre Redes Neuronales Convolucionales y el algoritmo metaheurístico de Optimización por Enjambre de Partículas; para la clasificación de arritmias cardíacas. El metaheurístico se encargó de optimizar la arquitectura de capas de la red neuronal, a través de la minización de la pérdida durante el entrenamiento y prueba. Los datos se obtuvieron del MIT-BIH Arrhythmia dataset, donde se describen cinco categorías de arritmias. Los resultados logrados demostraron que el metaheurístico es un algoritmo confiable en la búsqueda de la mejor arquitectura de capas, logrando obtener una exactitud del 97%, lo que significa que el uso de técnicas metaheurísticas es una opción que se debe tomar en consideración a la hora de optimizar el rendimiento de las redes neuronales convolucionales.

show abstract

A Hybrid Barnacles Mating Optimizer Algorithm With Support Vector Machines for Gene Selection of Microarray Cancer Classification

Cited by 63 publications

References 31 publications

Application of Multipopulation Genetic Algorithm in Industrial Special Clothing Design

Application of Multipopulation Genetic Algorithm in Industrial Special Clothing Design

Real-Time Facemask Detection for Preventing COVID-19 Spread Using Transfer Learning Based Deep Neural Network

Clasificación de Arritmias Cardíacas mediante Redes Neuronales Convolucionales y Optimización por Enjambre de Partículas

Contact Info

Product

Resources

About