Feature selection of medical dataset using african vultures optimization algorithm
Feature selection is one of the popular techniques used to reduce the number of features by
eliminating noisy, unreliable, and unnecessary data without affecting the classification …
eliminating noisy, unreliable, and unnecessary data without affecting the classification …
Optimized Machine Learning Model with Modified Particle Swarm Optimization for Data Classification
Metaheuristic search algorithms (MSAs) receive increasing popularity in recent year due to
its excellent capability of solving complex real-world optimization problems without …
its excellent capability of solving complex real-world optimization problems without …
[PDF][PDF] Classification of wafer defects with optimized deep learning model
Wafer defect inspection is one of the crucial semiconductor processing technologies
because it can help to identify the surface defects in the process and eventually improve the …
because it can help to identify the surface defects in the process and eventually improve the …
Hyperparameter Optimization of Deep Learning Model: A Case Study of COVID-19 Diagnosis
The global impact of COVID-19, which has affected over 700 million individuals,
necessitates the development of automated diagnostic tools for rapid screening using …
necessitates the development of automated diagnostic tools for rapid screening using …
Wrapper-Based Feature Selection Using Sperm Swarm Optimization: A Comparative Study
Feature selection is a vital technique that enhances the quality of input datasets by reducing
redundancy, noise, and inaccuracies without compromising classifier accuracy. The …
redundancy, noise, and inaccuracies without compromising classifier accuracy. The …
A Modified African Vultures Optimization Algorithm for Enhanced Feature Selection
Feature selection is a reliable technique for reducing redundant, noisy, or inaccurate
features in raw input datasets without compromising classifier accuracy. Integrating …
features in raw input datasets without compromising classifier accuracy. Integrating …
Optimization Strategies for Training Artificial Neural Network: A Case Study in Medical Classification
Backpropagation (BP) is a widely embraced method for training artificial neural networks
(ANNs) in classification and regression tasks. However, its efficacy diminishes when …
(ANNs) in classification and regression tasks. However, its efficacy diminishes when …
Development of new solid insulating material with aid of alkyl phenolic resin for a liquid-immersed transformer
V Jindal, J Singh - Arabian Journal for Science and Engineering, 2020 - Springer
The continuous increase in power requirement has created new challenges for insulating
materials. In a construction of a power transformer, the paper insulation is most vulnerable to …
materials. In a construction of a power transformer, the paper insulation is most vulnerable to …
Insulator Coating To Improve Outdoor Insulator Performance
RA Diantari, U Khayam - 2023 4th International Conference …, 2023 - ieeexplore.ieee.org
Disturbance to outdoor insulators is caused by several factors and is generally caused by
external factors, namely environmental factors. These environmental factors greatly affect …
external factors, namely environmental factors. These environmental factors greatly affect …
Review of Insulator Coatings to Improve Outdoor Insulator Performance
RA Diantari, U Khayam - 2022 IEEE International …, 2022 - ieeexplore.ieee.org
Insulator is one of the equipment that is very important in the distribution of electric power
systems. Insulation is needed to separate two or more live electric conductors so that …
systems. Insulation is needed to separate two or more live electric conductors so that …